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update aclanthology

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  1. .gitignore +3 -0
  2. Makefile +22 -0
  3. README.md +55 -2
  4. requirements.txt +2 -0
  5. results/doc-paper-list.md +117 -0
  6. results/ee-paper-list.md +396 -0
  7. run.py +45 -0
  8. scripts/download_cache.py +11 -0
  9. scripts/get_aclanthology.sh +34 -0
  10. src/__init__.py +0 -0
  11. src/engine.py +67 -0
  12. src/interfaces/__init__.py +26 -0
  13. src/interfaces/aclanthology.py +44 -0
  14. src/interfaces/arxiv.py +0 -0
  15. src/interfaces/dblp.py +0 -0
  16. src/utils.py +151 -0
  17. tests/__init__.py +0 -0
  18. tests/test_utils.py +216 -0
  19. tox.ini +7 -0
.gitignore CHANGED
@@ -127,3 +127,6 @@ dmypy.json
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  # Pyre type checker
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  .pyre/
 
 
 
 
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  # Pyre type checker
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  .pyre/
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+
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+ cache/
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+ .coverage
Makefile ADDED
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+ all: format clean test
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+ echo 'finished'
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+
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+ .PHONY: format
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+ format:
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+ isort --profile black --filter-files . -s cache/
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+ black --exclude cache/ .
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+
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+ .PHONY: test
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+ test:
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+ coverage run --source src -m pytest -vv tests/
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+ coverage report -m
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+ flake8
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+
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+ .PHONY: clean
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+ clean:
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+ rm -rf build/
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+ rm -rf dist/
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+ rm -rf *.egg-info/
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+ rm -f .coverage
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+ rm -f coverage.xml
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+ find . | grep -E '(__pycache__|\.pyc|\.pyo$$)' | xargs rm -rf
README.md CHANGED
@@ -1,2 +1,55 @@
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- # paper-hero
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- A toolkit to help find relevant papers from aclanthology, arXiv and dblp.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # 💪 Paper Hero
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+
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+ A toolkit to help search papers from aclanthology, arXiv and dblp.
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+
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+ ## 🌴 Setup
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+
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+ 1. Make sure you have [Git](https://git-scm.com/) and [Python](https://www.python.org/downloads/) 3.10.8 installed (or Python >= 3.9).
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+ 2. Install dependencies: `pip install -r requirements.txt`
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+
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+ ## 🚀 QuickStart
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+
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+ Run the example in `run.py`:
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+
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+ ```bash
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+ $ python run.py
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+ ```
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+
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+ ```python
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+ from src.interfaces.aclanthology import AclanthologyPaperList
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+ from src.utils import dump_paper_list_to_markdown_checklist
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+
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+ if __name__ == "__main__":
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+ # use `bash scripts/get_aclanthology.sh` to download and prepare anthology data
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+ paper_list = AclanthologyPaperList("cache/aclanthology.json")
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+ ee_query = {
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+ "title": [
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+ # Any of the strings below is matched
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+ ["information extraction"],
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+ ["event", "extraction"], # title must include `event` and `extraction`
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+ ["event", "argument", "extraction"],
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+ ["event", "detection"],
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+ ["event", "classification"],
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+ ["event", "tracking"],
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+ ["event", "relation", "extraction"],
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+ ],
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+ # Besides the title constraint, venue must also meet the needs
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+ "venue": [
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+ ["acl"],
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+ ["emnlp"],
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+ ["naacl"],
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+ ["coling"],
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+ ["findings"],
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+ ["tacl"],
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+ ["cl"],
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+ ],
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+ }
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+ ee_papers = paper_list.search(ee_query)
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+ dump_paper_list_to_markdown_checklist(ee_papers, "results/ee-paper-list.md")
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+ ```
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+
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+ ## 🗺️ Roadmap
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+
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+ - [x] aclanthology
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+ - [ ] arXiv
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+ - [ ] dblp
requirements.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
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+ tqdm
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+ requests
results/doc-paper-list.md ADDED
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+ - [ ] [FINDINGS, 2022] [ArgGen: Prompting Text Generation Models for Document-Level Event-Argument Aggregation](https://aclanthology.org/2022.findings-aacl.37)
2
+ - [ ] [COLING, 2022] [Key Mention Pairs Guided Document-Level Relation Extraction](https://aclanthology.org/2022.coling-1.165)
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+ - [ ] [COLING, 2022] [Document-level Biomedical Relation Extraction Based on Multi-Dimensional Fusion Information and Multi-Granularity Logical Reasoning](https://aclanthology.org/2022.coling-1.183)
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+ - [ ] [COLING, 2022] [ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification](https://aclanthology.org/2022.coling-1.185)
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+ - [ ] [COLING, 2022] [Document-Level Relation Extraction via Pair-Aware and Entity-Enhanced Representation Learning](https://aclanthology.org/2022.coling-1.213)
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+ - [ ] [COLING, 2022] [CLIO: Role-interactive Multi-event Head Attention Network for Document-level Event Extraction](https://aclanthology.org/2022.coling-1.221)
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+ - [ ] [COLING, 2022] [Document-level Event Factuality Identification via Machine Reading Comprehension Frameworks with Transfer Learning](https://aclanthology.org/2022.coling-1.231)
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+ - [ ] [COLING, 2022] [CoDoNMT: Modeling Cohesion Devices for Document-Level Neural Machine Translation](https://aclanthology.org/2022.coling-1.462)
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+ - [ ] [FINDINGS, 2022] [DOCmT5: Document-Level Pretraining of Multilingual Language Models](https://aclanthology.org/2022.findings-naacl.32)
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+ - [ ] [FINDINGS, 2022] [Learn To Remember: Transformer with Recurrent Memory for Document-Level Machine Translation](https://aclanthology.org/2022.findings-naacl.105)
11
+ - [ ] [FINDINGS, 2022] [EA2E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](https://aclanthology.org/2022.findings-naacl.202)
12
+ - [ ] [NAACL, 2022] [NewsEdits: A News Article Revision Dataset and a Novel Document-Level Reasoning Challenge](https://aclanthology.org/2022.naacl-main.10)
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+ - [ ] [NAACL, 2022] [DocTime: A Document-level Temporal Dependency Graph Parser](https://aclanthology.org/2022.naacl-main.73)
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+ - [ ] [NAACL, 2022] [Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction](https://aclanthology.org/2022.naacl-main.109)
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+ - [ ] [NAACL, 2022] [BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation](https://aclanthology.org/2022.naacl-main.111)
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+ - [ ] [NAACL, 2022] [SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction](https://aclanthology.org/2022.naacl-main.171)
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+ - [ ] [NAACL, 2022] [Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization](https://aclanthology.org/2022.naacl-main.199)
18
+ - [ ] [NAACL, 2022] [Document-Level Relation Extraction with Sentences Importance Estimation and Focusing](https://aclanthology.org/2022.naacl-main.212)
19
+ - [ ] [NAACL, 2022] [Document-Level Event Argument Extraction by Leveraging Redundant Information and Closed Boundary Loss](https://aclanthology.org/2022.naacl-main.222)
20
+ - [ ] [NAACL, 2022] [DocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction](https://aclanthology.org/2022.naacl-main.291)
21
+ - [ ] [NAACL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](https://aclanthology.org/2022.naacl-main.367)
22
+ - [ ] [NAACL, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](https://aclanthology.org/2022.naacl-main.370)
23
+ - [ ] [NAACL, 2022] [Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction](https://aclanthology.org/2022.naacl-main.395)
24
+ - [ ] [NAACL, 2022] [Few-Shot Document-Level Relation Extraction](https://aclanthology.org/2022.naacl-main.421)
25
+ - [ ] [ACL, 2022] [Automatic Error Analysis for Document-level Information Extraction](https://aclanthology.org/2022.acl-long.274)
26
+ - [ ] [ACL, 2022] [Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents](https://aclanthology.org/2022.acl-long.287)
27
+ - [ ] [ACL, 2022] [Dynamic Global Memory for Document-level Argument Extraction](https://aclanthology.org/2022.acl-long.361)
28
+ - [ ] [ACL, 2022] [Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution](https://aclanthology.org/2022.acl-short.88)
29
+ - [ ] [FINDINGS, 2022] [Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion](https://aclanthology.org/2022.findings-acl.23)
30
+ - [ ] [FINDINGS, 2022] [Document-Level Event Argument Extraction via Optimal Transport](https://aclanthology.org/2022.findings-acl.130)
31
+ - [ ] [FINDINGS, 2022] [Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation](https://aclanthology.org/2022.findings-acl.132)
32
+ - [ ] [FINDINGS, 2022] [Rethinking Document-level Neural Machine Translation](https://aclanthology.org/2022.findings-acl.279)
33
+ - [ ] [FINDINGS, 2021] [Exploring Sentence Community for Document-Level Event Extraction](https://aclanthology.org/2021.findings-emnlp.32)
34
+ - [ ] [FINDINGS, 2021] [Bidirectional Hierarchical Attention Networks based on Document-level Context for Emotion Cause Extraction](https://aclanthology.org/2021.findings-emnlp.51)
35
+ - [ ] [FINDINGS, 2021] [Towards Document-Level Paraphrase Generation with Sentence Rewriting and Reordering](https://aclanthology.org/2021.findings-emnlp.89)
36
+ - [ ] [FINDINGS, 2021] [ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts](https://aclanthology.org/2021.findings-emnlp.164)
37
+ - [ ] [EMNLP, 2021] [Learning Logic Rules for Document-Level Relation Extraction](https://aclanthology.org/2021.emnlp-main.95)
38
+ - [ ] [EMNLP, 2021] [Coupling Context Modeling with Zero Pronoun Recovering for Document-Level Natural Language Generation](https://aclanthology.org/2021.emnlp-main.197)
39
+ - [ ] [EMNLP, 2021] [Uncertain Local-to-Global Networks for Document-Level Event Factuality Identification](https://aclanthology.org/2021.emnlp-main.207)
40
+ - [ ] [EMNLP, 2021] [Encouraging Lexical Translation Consistency for Document-Level Neural Machine Translation](https://aclanthology.org/2021.emnlp-main.262)
41
+ - [ ] [EMNLP, 2021] [Document-level Entity-based Extraction as Template Generation](https://aclanthology.org/2021.emnlp-main.426)
42
+ - [ ] [EMNLP, 2021] [Modular Self-Supervision for Document-Level Relation Extraction](https://aclanthology.org/2021.emnlp-main.429)
43
+ - [ ] [EMNLP, 2021] [Modeling Document-Level Context for Event Detection via Important Context Selection](https://aclanthology.org/2021.emnlp-main.439)
44
+ - [ ] [EMNLP, 2021] [Document-Level Text Simplification: Dataset, Criteria and Baseline](https://aclanthology.org/2021.emnlp-main.630)
45
+ - [ ] [ACL, 2021] [G-Transformer for Document-Level Machine Translation](https://aclanthology.org/2021.acl-long.267)
46
+ - [ ] [ACL, 2021] [Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker](https://aclanthology.org/2021.acl-long.274)
47
+ - [ ] [ACL, 2021] [Document-level Event Extraction via Parallel Prediction Networks](https://aclanthology.org/2021.acl-long.492)
48
+ - [ ] [ACL, 2021] [TIMERS: Document-level Temporal Relation Extraction](https://aclanthology.org/2021.acl-short.67)
49
+ - [ ] [ACL, 2021] [Joint Detection and Coreference Resolution of Entities and Events with Document-level Context Aggregation](https://aclanthology.org/2021.acl-srw.18)
50
+ - [ ] [FINDINGS, 2021] [SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction](https://aclanthology.org/2021.findings-acl.47)
51
+ - [ ] [FINDINGS, 2021] [MRN: A Locally and Globally Mention-Based Reasoning Network for Document-Level Relation Extraction](https://aclanthology.org/2021.findings-acl.117)
52
+ - [ ] [FINDINGS, 2021] [Discriminative Reasoning for Document-level Relation Extraction](https://aclanthology.org/2021.findings-acl.144)
53
+ - [ ] [FINDINGS, 2021] [DocOIE: A Document-level Context-Aware Dataset for OpenIE](https://aclanthology.org/2021.findings-acl.210)
54
+ - [ ] [FINDINGS, 2021] [A Neural Edge-Editing Approach for Document-Level Relation Graph Extraction](https://aclanthology.org/2021.findings-acl.234)
55
+ - [ ] [FINDINGS, 2021] [DocNLI: A Large-scale Dataset for Document-level Natural Language Inference](https://aclanthology.org/2021.findings-acl.435)
56
+ - [ ] [NAACL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](https://aclanthology.org/2021.naacl-main.69)
57
+ - [ ] [NAACL, 2021] [Why Do Document-Level Polarity Classifiers Fail?](https://aclanthology.org/2021.naacl-main.143)
58
+ - [ ] [NAACL, 2021] [Graph Convolutional Networks for Event Causality Identification with Rich Document-level Structures](https://aclanthology.org/2021.naacl-main.273)
59
+ - [ ] [NAACL, 2021] [Multi-Hop Transformer for Document-Level Machine Translation](https://aclanthology.org/2021.naacl-main.309)
60
+ - [ ] [NAACL, 2021] [Context-aware Decoder for Neural Machine Translation using a Target-side Document-Level Language Model](https://aclanthology.org/2021.naacl-main.461)
61
+ - [ ] [NAACL, 2021] [ActiveAnno: General-Purpose Document-Level Annotation Tool with Active Learning Integration](https://aclanthology.org/2021.naacl-demos.12)
62
+ - [ ] [TACL, 2020] [Better Document-Level Machine Translation with Bayes’ Rule](https://aclanthology.org/2020.tacl-1.23)
63
+ - [ ] [COLING, 2020] [Graph Enhanced Dual Attention Network for Document-Level Relation Extraction](https://aclanthology.org/2020.coling-main.136)
64
+ - [ ] [COLING, 2020] [Document-level Relation Extraction with Dual-tier Heterogeneous Graph](https://aclanthology.org/2020.coling-main.143)
65
+ - [ ] [COLING, 2020] [A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme Information](https://aclanthology.org/2020.coling-main.388)
66
+ - [ ] [COLING, 2020] [Leveraging Discourse Rewards for Document-Level Neural Machine Translation](https://aclanthology.org/2020.coling-main.395)
67
+ - [ ] [COLING, 2020] [Global Context-enhanced Graph Convolutional Networks for Document-level Relation Extraction](https://aclanthology.org/2020.coling-main.461)
68
+ - [ ] [COLING, 2020] [Improving Document-Level Sentiment Analysis with User and Product Context](https://aclanthology.org/2020.coling-main.590)
69
+ - [ ] [EMNLP, 2020] [Long-Short Term Masking Transformer: A Simple but Effective Baseline for Document-level Neural Machine Translation](https://aclanthology.org/2020.emnlp-main.81)
70
+ - [ ] [EMNLP, 2020] [Double Graph Based Reasoning for Document-level Relation Extraction](https://aclanthology.org/2020.emnlp-main.127)
71
+ - [ ] [EMNLP, 2020] [Dynamic Context Selection for Document-level Neural Machine Translation via Reinforcement Learning](https://aclanthology.org/2020.emnlp-main.175)
72
+ - [ ] [EMNLP, 2020] [Denoising Relation Extraction from Document-level Distant Supervision](https://aclanthology.org/2020.emnlp-main.300)
73
+ - [ ] [EMNLP, 2020] [Global-to-Local Neural Networks for Document-Level Relation Extraction](https://aclanthology.org/2020.emnlp-main.303)
74
+ - [ ] [EMNLP, 2020] [Substance over Style: Document-Level Targeted Content Transfer](https://aclanthology.org/2020.emnlp-main.526)
75
+ - [ ] [EMNLP, 2020] [Diversified Multiple Instance Learning for Document-Level Multi-Aspect Sentiment Classification](https://aclanthology.org/2020.emnlp-main.570)
76
+ - [ ] [FINDINGS, 2020] [The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction](https://aclanthology.org/2020.findings-emnlp.409)
77
+ - [ ] [ACL, 2020] [Reasoning with Latent Structure Refinement for Document-Level Relation Extraction](https://aclanthology.org/2020.acl-main.141)
78
+ - [ ] [ACL, 2020] [SPECTER: Document-level Representation Learning using Citation-informed Transformers](https://aclanthology.org/2020.acl-main.207)
79
+ - [ ] [ACL, 2020] [A Simple and Effective Unified Encoder for Document-Level Machine Translation](https://aclanthology.org/2020.acl-main.321)
80
+ - [ ] [ACL, 2020] [Aspect Sentiment Classification with Document-level Sentiment Preference Modeling](https://aclanthology.org/2020.acl-main.338)
81
+ - [ ] [ACL, 2020] [Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering](https://aclanthology.org/2020.acl-main.501)
82
+ - [ ] [ACL, 2020] [SciREX: A Challenge Dataset for Document-Level Information Extraction](https://aclanthology.org/2020.acl-main.670)
83
+ - [ ] [ACL, 2020] [Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding](https://aclanthology.org/2020.acl-main.714)
84
+ - [ ] [EMNLP, 2019] [Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction](https://aclanthology.org/D19-1032)
85
+ - [ ] [EMNLP, 2019] [Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level Translation](https://aclanthology.org/D19-1164)
86
+ - [ ] [EMNLP, 2019] [Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation](https://aclanthology.org/D19-1168)
87
+ - [ ] [EMNLP, 2019] [Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs](https://aclanthology.org/D19-1498)
88
+ - [ ] [EMNLP, 2019] [Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning](https://aclanthology.org/D19-1560)
89
+ - [ ] [ACL, 2019] [DocRED: A Large-Scale Document-Level Relation Extraction Dataset](https://aclanthology.org/P19-1074)
90
+ - [ ] [ACL, 2019] [Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network](https://aclanthology.org/P19-1423)
91
+ - [ ] [NAACL, 2019] [Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation](https://aclanthology.org/N19-1033)
92
+ - [ ] [NAACL, 2019] [A Variational Approach to Weakly Supervised Document-Level Multi-Aspect Sentiment Classification](https://aclanthology.org/N19-1036)
93
+ - [ ] [NAACL, 2019] [Word-Node2Vec: Improving Word Embedding with Document-Level Non-Local Word Co-occurrences](https://aclanthology.org/N19-1109)
94
+ - [ ] [NAACL, 2019] [Modeling Document-level Causal Structures for Event Causal Relation Identification](https://aclanthology.org/N19-1179)
95
+ - [ ] [NAACL, 2019] [Document-Level Event Factuality Identification via Adversarial Neural Network](https://aclanthology.org/N19-1287)
96
+ - [ ] [NAACL, 2019] [Document-Level N-ary Relation Extraction with Multiscale Representation Learning](https://aclanthology.org/N19-1370)
97
+ - [ ] [EMNLP, 2018] [Improving the Transformer Translation Model with Document-Level Context](https://aclanthology.org/D18-1049)
98
+ - [ ] [EMNLP, 2018] [Document-Level Neural Machine Translation with Hierarchical Attention Networks](https://aclanthology.org/D18-1325)
99
+ - [ ] [EMNLP, 2018] [Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation](https://aclanthology.org/D18-1512)
100
+ - [ ] [COLING, 2018] [Document-level Multi-aspect Sentiment Classification by Jointly Modeling Users, Aspects, and Overall Ratings](https://aclanthology.org/C18-1079)
101
+ - [ ] [ACL, 2018] [DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data](https://aclanthology.org/P18-4009)
102
+ - [ ] [EMNLP, 2017] [Document-Level Multi-Aspect Sentiment Classification as Machine Comprehension](https://aclanthology.org/D17-1217)
103
+ - [ ] [EMNLP, 2016] [Cached Long Short-Term Memory Neural Networks for Document-Level Sentiment Classification](https://aclanthology.org/D16-1172)
104
+ - [ ] [ACL, 2016] [Document-level Sentiment Inference with Social, Faction, and Discourse Context](https://aclanthology.org/P16-1032)
105
+ - [ ] [EMNLP, 2015] [Better Document-level Sentiment Analysis from RST Discourse Parsing](https://aclanthology.org/D15-1263)
106
+ - [ ] [NAACL, 2015] [Discourse and Document-level Information for Evaluating Language Output Tasks](https://aclanthology.org/N15-2016)
107
+ - [ ] [ACL, 2014] [Effective Document-Level Features for Chinese Patent Word Segmentation](https://aclanthology.org/P14-2033)
108
+ - [ ] [EMNLP, 2013] [Lexical Chain Based Cohesion Models for Document-Level Statistical Machine Translation](https://aclanthology.org/D13-1163)
109
+ - [ ] [ACL, 2013] [Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis](https://aclanthology.org/P13-1048)
110
+ - [ ] [ACL, 2013] [Bilingual Lexical Cohesion Trigger Model for Document-Level Machine Translation](https://aclanthology.org/P13-2068)
111
+ - [ ] [ACL, 2013] [Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation](https://aclanthology.org/P13-4033)
112
+ - [ ] [ACL, 2012] [Identifying High-Impact Sub-Structures for Convolution Kernels in Document-level Sentiment Classification](https://aclanthology.org/P12-2066)
113
+ - [ ] [EMNLP, 2011] [Learning Local Content Shift Detectors from Document-level Information](https://aclanthology.org/D11-1070)
114
+ - [ ] [EMNLP, 2011] [Cache-based Document-level Statistical Machine Translation](https://aclanthology.org/D11-1084)
115
+ - [ ] [ACL, 2011] [Reordering Constraint Based on Document-Level Context](https://aclanthology.org/P11-2076)
116
+ - [ ] [EMNLP, 2010] [Multi-Level Structured Models for Document-Level Sentiment Classification](https://aclanthology.org/D10-1102)
117
+ - [ ] [ACL, 2008] [Learning Document-Level Semantic Properties from Free-Text Annotations](https://aclanthology.org/P08-1031)
results/ee-paper-list.md ADDED
@@ -0,0 +1,396 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ - [ ] [COLING, 2022] [Different Data, Different Modalities! Reinforced Data Splitting for Effective Multimodal Information Extraction from Social Media Posts](https://aclanthology.org/2022.coling-1.160)
2
+ - [ ] [COLING, 2022] [KiPT: Knowledge-injected Prompt Tuning for Event Detection](https://aclanthology.org/2022.coling-1.169)
3
+ - [ ] [COLING, 2022] [OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction](https://aclanthology.org/2022.coling-1.170)
4
+ - [ ] [COLING, 2022] [Event Detection with Dual Relational Graph Attention Networks](https://aclanthology.org/2022.coling-1.172)
5
+ - [ ] [COLING, 2022] [A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck](https://aclanthology.org/2022.coling-1.173)
6
+ - [ ] [COLING, 2022] [A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck](https://aclanthology.org/2022.coling-1.173)
7
+ - [ ] [COLING, 2022] [Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection](https://aclanthology.org/2022.coling-1.189)
8
+ - [ ] [COLING, 2022] [Event Causality Extraction with Event Argument Correlations](https://aclanthology.org/2022.coling-1.201)
9
+ - [ ] [COLING, 2022] [Event Causality Extraction with Event Argument Correlations](https://aclanthology.org/2022.coling-1.201)
10
+ - [ ] [COLING, 2022] [DESED: Dialogue-based Explanation for Sentence-level Event Detection](https://aclanthology.org/2022.coling-1.219)
11
+ - [ ] [COLING, 2022] [CLIO: Role-interactive Multi-event Head Attention Network for Document-level Event Extraction](https://aclanthology.org/2022.coling-1.221)
12
+ - [ ] [COLING, 2022] [Unregulated Chinese-to-English Data Expansion Does NOT Work for Neural Event Detection](https://aclanthology.org/2022.coling-1.232)
13
+ - [ ] [COLING, 2022] [Text-to-Text Extraction and Verbalization of Biomedical Event Graphs](https://aclanthology.org/2022.coling-1.238)
14
+ - [ ] [COLING, 2022] [Event Extraction in Video Transcripts](https://aclanthology.org/2022.coling-1.625)
15
+ - [ ] [FINDINGS, 2022] [Event Detection for Suicide Understanding](https://aclanthology.org/2022.findings-naacl.150)
16
+ - [ ] [FINDINGS, 2022] [Zero-Shot Event Detection Based on Ordered Contrastive Learning and Prompt-Based Prediction](https://aclanthology.org/2022.findings-naacl.196)
17
+ - [ ] [FINDINGS, 2022] [EA2E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](https://aclanthology.org/2022.findings-naacl.202)
18
+ - [ ] [FINDINGS, 2022] [EA2E: Improving Consistency with Event Awareness for Document-Level Argument Extraction](https://aclanthology.org/2022.findings-naacl.202)
19
+ - [ ] [NAACL, 2022] [Cross-document Misinformation Detection based on Event Graph Reasoning](https://aclanthology.org/2022.naacl-main.40)
20
+ - [ ] [NAACL, 2022] [CompactIE: Compact Facts in Open Information Extraction](https://aclanthology.org/2022.naacl-main.65)
21
+ - [ ] [NAACL, 2022] [DEGREE: A Data-Efficient Generation-Based Event Extraction Model](https://aclanthology.org/2022.naacl-main.138)
22
+ - [ ] [NAACL, 2022] [MINION: a Large-Scale and Diverse Dataset for Multilingual Event Detection](https://aclanthology.org/2022.naacl-main.166)
23
+ - [ ] [NAACL, 2022] [Document-Level Event Argument Extraction by Leveraging Redundant Information and Closed Boundary Loss](https://aclanthology.org/2022.naacl-main.222)
24
+ - [ ] [NAACL, 2022] [Document-Level Event Argument Extraction by Leveraging Redundant Information and Closed Boundary Loss](https://aclanthology.org/2022.naacl-main.222)
25
+ - [ ] [NAACL, 2022] [GMN: Generative Multi-modal Network for Practical Document Information Extraction](https://aclanthology.org/2022.naacl-main.276)
26
+ - [ ] [NAACL, 2022] [DocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction](https://aclanthology.org/2022.naacl-main.291)
27
+ - [ ] [NAACL, 2022] [GenIE: Generative Information Extraction](https://aclanthology.org/2022.naacl-main.342)
28
+ - [ ] [NAACL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](https://aclanthology.org/2022.naacl-main.367)
29
+ - [ ] [NAACL, 2022] [RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction](https://aclanthology.org/2022.naacl-main.367)
30
+ - [ ] [NAACL, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](https://aclanthology.org/2022.naacl-main.370)
31
+ - [ ] [NAACL, 2022] [A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction](https://aclanthology.org/2022.naacl-main.370)
32
+ - [ ] [NAACL, 2022] [Cross-Lingual Event Detection via Optimized Adversarial Training](https://aclanthology.org/2022.naacl-main.409)
33
+ - [ ] [NAACL, 2022] [ZS4IE: A toolkit for Zero-Shot Information Extraction with simple Verbalizations](https://aclanthology.org/2022.naacl-demo.4)
34
+ - [ ] [NAACL, 2022] [A Human-machine Interface for Few-shot Rule Synthesis for Information Extraction](https://aclanthology.org/2022.naacl-demo.8)
35
+ - [ ] [NAACL, 2022] [FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction](https://aclanthology.org/2022.naacl-demo.14)
36
+ - [ ] [NAACL, 2022] [New Frontiers of Information Extraction](https://aclanthology.org/2022.naacl-tutorials.3)
37
+ - [ ] [ACL, 2022] [Legal Judgment Prediction via Event Extraction with Constraints](https://aclanthology.org/2022.acl-long.48)
38
+ - [ ] [ACL, 2022] [Alignment-Augmented Consistent Translation for Multilingual Open Information Extraction](https://aclanthology.org/2022.acl-long.179)
39
+ - [ ] [ACL, 2022] [Text-to-Table: A New Way of Information Extraction](https://aclanthology.org/2022.acl-long.180)
40
+ - [ ] [ACL, 2022] [FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction](https://aclanthology.org/2022.acl-long.260)
41
+ - [ ] [ACL, 2022] [Automatic Error Analysis for Document-level Information Extraction](https://aclanthology.org/2022.acl-long.274)
42
+ - [ ] [ACL, 2022] [BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation](https://aclanthology.org/2022.acl-long.307)
43
+ - [ ] [ACL, 2022] [Saliency as Evidence: Event Detection with Trigger Saliency Attribution](https://aclanthology.org/2022.acl-long.313)
44
+ - [ ] [ACL, 2022] [Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction](https://aclanthology.org/2022.acl-long.317)
45
+ - [ ] [ACL, 2022] [Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction](https://aclanthology.org/2022.acl-long.317)
46
+ - [ ] [ACL, 2022] [Dynamic Prefix-Tuning for Generative Template-based Event Extraction](https://aclanthology.org/2022.acl-long.358)
47
+ - [ ] [ACL, 2022] [Unified Structure Generation for Universal Information Extraction](https://aclanthology.org/2022.acl-long.395)
48
+ - [ ] [ACL, 2022] [OIE@OIA: an Adaptable and Efficient Open Information Extraction Framework](https://aclanthology.org/2022.acl-long.430)
49
+ - [ ] [ACL, 2022] [Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction](https://aclanthology.org/2022.acl-long.466)
50
+ - [ ] [ACL, 2022] [Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction](https://aclanthology.org/2022.acl-long.466)
51
+ - [ ] [ACL, 2022] [MILIE: Modular & Iterative Multilingual Open Information Extraction](https://aclanthology.org/2022.acl-long.478)
52
+ - [ ] [ACL, 2022] [AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark](https://aclanthology.org/2022.acl-demo.5)
53
+ - [ ] [FINDINGS, 2022] [Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding](https://aclanthology.org/2022.findings-acl.16)
54
+ - [ ] [FINDINGS, 2022] [LEVEN: A Large-Scale Chinese Legal Event Detection Dataset](https://aclanthology.org/2022.findings-acl.17)
55
+ - [ ] [FINDINGS, 2022] [Document-Level Event Argument Extraction via Optimal Transport](https://aclanthology.org/2022.findings-acl.130)
56
+ - [ ] [FINDINGS, 2022] [Document-Level Event Argument Extraction via Optimal Transport](https://aclanthology.org/2022.findings-acl.130)
57
+ - [ ] [FINDINGS, 2021] [Joint Multimedia Event Extraction from Video and Article](https://aclanthology.org/2021.findings-emnlp.8)
58
+ - [ ] [FINDINGS, 2021] [Self-Attention Graph Residual Convolutional Networks for Event Detection with dependency relations](https://aclanthology.org/2021.findings-emnlp.28)
59
+ - [ ] [FINDINGS, 2021] [Exploring Sentence Community for Document-Level Event Extraction](https://aclanthology.org/2021.findings-emnlp.32)
60
+ - [ ] [EMNLP, 2021] [Zero-Shot Information Extraction as a Unified Text-to-Triple Translation](https://aclanthology.org/2021.emnlp-main.94)
61
+ - [ ] [EMNLP, 2021] [Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction](https://aclanthology.org/2021.emnlp-main.149)
62
+ - [ ] [EMNLP, 2021] [Treasures Outside Contexts: Improving Event Detection via Global Statistics](https://aclanthology.org/2021.emnlp-main.206)
63
+ - [ ] [EMNLP, 2021] [Machine Reading Comprehension as Data Augmentation: A Case Study on Implicit Event Argument Extraction](https://aclanthology.org/2021.emnlp-main.214)
64
+ - [ ] [EMNLP, 2021] [Machine Reading Comprehension as Data Augmentation: A Case Study on Implicit Event Argument Extraction](https://aclanthology.org/2021.emnlp-main.214)
65
+ - [ ] [EMNLP, 2021] [Cost-effective End-to-end Information Extraction for Semi-structured Document Images](https://aclanthology.org/2021.emnlp-main.271)
66
+ - [ ] [EMNLP, 2021] [Learning Prototype Representations Across Few-Shot Tasks for Event Detection](https://aclanthology.org/2021.emnlp-main.427)
67
+ - [ ] [EMNLP, 2021] [Lifelong Event Detection with Knowledge Transfer](https://aclanthology.org/2021.emnlp-main.428)
68
+ - [ ] [EMNLP, 2021] [Learning from Noisy Labels for Entity-Centric Information Extraction](https://aclanthology.org/2021.emnlp-main.437)
69
+ - [ ] [EMNLP, 2021] [Modeling Document-Level Context for Event Detection via Important Context Selection](https://aclanthology.org/2021.emnlp-main.439)
70
+ - [ ] [EMNLP, 2021] [Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments](https://aclanthology.org/2021.emnlp-main.440)
71
+ - [ ] [EMNLP, 2021] [Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments](https://aclanthology.org/2021.emnlp-main.440)
72
+ - [ ] [EMNLP, 2021] [Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention](https://aclanthology.org/2021.emnlp-main.637)
73
+ - [ ] [EMNLP, 2021] [Uncovering Main Causalities for Long-tailed Information Extraction](https://aclanthology.org/2021.emnlp-main.763)
74
+ - [ ] [EMNLP, 2021] [Maximal Clique Based Non-Autoregressive Open Information Extraction](https://aclanthology.org/2021.emnlp-main.764)
75
+ - [ ] [EMNLP, 2021] [Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction](https://aclanthology.org/2021.emnlp-main.815)
76
+ - [ ] [EMNLP, 2021] [Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction](https://aclanthology.org/2021.emnlp-main.815)
77
+ - [ ] [ACL, 2021] [CitationIE: Leveraging the Citation Graph for Scientific Information Extraction](https://aclanthology.org/2021.acl-long.59)
78
+ - [ ] [ACL, 2021] [From Discourse to Narrative: Knowledge Projection for Event Relation Extraction](https://aclanthology.org/2021.acl-long.60)
79
+ - [ ] [ACL, 2021] [From Discourse to Narrative: Knowledge Projection for Event Relation Extraction](https://aclanthology.org/2021.acl-long.60)
80
+ - [ ] [ACL, 2021] [Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](https://aclanthology.org/2021.acl-long.217)
81
+ - [ ] [ACL, 2021] [OntoED: Low-resource Event Detection with Ontology Embedding](https://aclanthology.org/2021.acl-long.220)
82
+ - [ ] [ACL, 2021] [Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker](https://aclanthology.org/2021.acl-long.274)
83
+ - [ ] [ACL, 2021] [Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction](https://aclanthology.org/2021.acl-long.360)
84
+ - [ ] [ACL, 2021] [Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction](https://aclanthology.org/2021.acl-long.360)
85
+ - [ ] [ACL, 2021] [CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction](https://aclanthology.org/2021.acl-long.363)
86
+ - [ ] [ACL, 2021] [MLBiNet: A Cross-Sentence Collective Event Detection Network](https://aclanthology.org/2021.acl-long.373)
87
+ - [ ] [ACL, 2021] [Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation](https://aclanthology.org/2021.acl-long.489)
88
+ - [ ] [ACL, 2021] [Unleash GPT-2 Power for Event Detection](https://aclanthology.org/2021.acl-long.490)
89
+ - [ ] [ACL, 2021] [CLEVE: Contrastive Pre-training for Event Extraction](https://aclanthology.org/2021.acl-long.491)
90
+ - [ ] [ACL, 2021] [Document-level Event Extraction via Parallel Prediction Networks](https://aclanthology.org/2021.acl-long.492)
91
+ - [ ] [ACL, 2021] [ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction](https://aclanthology.org/2021.acl-short.41)
92
+ - [ ] [ACL, 2021] [Zero-shot Event Extraction via Transfer Learning: Challenges and Insights](https://aclanthology.org/2021.acl-short.42)
93
+ - [ ] [ACL, 2021] [CogIE: An Information Extraction Toolkit for Bridging Texts and CogNet](https://aclanthology.org/2021.acl-demo.11)
94
+ - [ ] [FINDINGS, 2021] [Few-Shot Event Detection with Prototypical Amortized Conditional Random Field](https://aclanthology.org/2021.findings-acl.3)
95
+ - [ ] [FINDINGS, 2021] [CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction](https://aclanthology.org/2021.findings-acl.14)
96
+ - [ ] [FINDINGS, 2021] [Spatial Dependency Parsing for Semi-Structured Document Information Extraction](https://aclanthology.org/2021.findings-acl.28)
97
+ - [ ] [FINDINGS, 2021] [A Dialogue-based Information Extraction System for Medical Insurance Assessment](https://aclanthology.org/2021.findings-acl.58)
98
+ - [ ] [FINDINGS, 2021] [Zero-shot Label-Aware Event Trigger and Argument Classification](https://aclanthology.org/2021.findings-acl.114)
99
+ - [ ] [FINDINGS, 2021] [Event Detection as Graph Parsing](https://aclanthology.org/2021.findings-acl.142)
100
+ - [ ] [FINDINGS, 2021] [Event Extraction from Historical Texts: A New Dataset for Black Rebellions](https://aclanthology.org/2021.findings-acl.211)
101
+ - [ ] [FINDINGS, 2021] [Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection](https://aclanthology.org/2021.findings-acl.214)
102
+ - [ ] [FINDINGS, 2021] [GrantRel: Grant Information Extraction via Joint Entity and Relation Extraction](https://aclanthology.org/2021.findings-acl.236)
103
+ - [ ] [FINDINGS, 2021] [Unsupervised Domain Adaptation for Event Detection using Domain-specific Adapters](https://aclanthology.org/2021.findings-acl.351)
104
+ - [ ] [FINDINGS, 2021] [Revisiting the Evaluation of End-to-end Event Extraction](https://aclanthology.org/2021.findings-acl.405)
105
+ - [ ] [NAACL, 2021] [Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks](https://aclanthology.org/2021.naacl-main.3)
106
+ - [ ] [NAACL, 2021] [Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction](https://aclanthology.org/2021.naacl-main.4)
107
+ - [ ] [NAACL, 2021] [Event Time Extraction and Propagation via Graph Attention Networks](https://aclanthology.org/2021.naacl-main.6)
108
+ - [ ] [NAACL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](https://aclanthology.org/2021.naacl-main.69)
109
+ - [ ] [NAACL, 2021] [Document-Level Event Argument Extraction by Conditional Generation](https://aclanthology.org/2021.naacl-main.69)
110
+ - [ ] [NAACL, 2021] [RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System](https://aclanthology.org/2021.naacl-demos.16)
111
+ - [ ] [NAACL, 2021] [RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System](https://aclanthology.org/2021.naacl-demos.16)
112
+ - [ ] [NAACL, 2021] [RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System](https://aclanthology.org/2021.naacl-demos.16)
113
+ - [ ] [COLING, 2020] [Hierarchical Chinese Legal event extraction via Pedal Attention Mechanism](https://aclanthology.org/2020.coling-main.9)
114
+ - [ ] [COLING, 2020] [Is Killed More Significant than Fled? A Contextual Model for Salient Event Detection](https://aclanthology.org/2020.coling-main.10)
115
+ - [ ] [COLING, 2020] [KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision](https://aclanthology.org/2020.coling-main.135)
116
+ - [ ] [COLING, 2020] [Joint Event Extraction with Hierarchical Policy Network](https://aclanthology.org/2020.coling-main.239)
117
+ - [ ] [EMNLP, 2020] [Event Extraction by Answering (Almost) Natural Questions](https://aclanthology.org/2020.emnlp-main.49)
118
+ - [ ] [EMNLP, 2020] [Incremental Event Detection via Knowledge Consolidation Networks](https://aclanthology.org/2020.emnlp-main.52)
119
+ - [ ] [EMNLP, 2020] [Semi-supervised New Event Type Induction and Event Detection](https://aclanthology.org/2020.emnlp-main.53)
120
+ - [ ] [EMNLP, 2020] [Event Extraction as Machine Reading Comprehension](https://aclanthology.org/2020.emnlp-main.128)
121
+ - [ ] [EMNLP, 2020] [MAVEN: A Massive General Domain Event Detection Dataset](https://aclanthology.org/2020.emnlp-main.129)
122
+ - [ ] [EMNLP, 2020] [OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction](https://aclanthology.org/2020.emnlp-main.306)
123
+ - [ ] [EMNLP, 2020] [An Empirical Study of Pre-trained Transformers for Arabic Information Extraction](https://aclanthology.org/2020.emnlp-main.382)
124
+ - [ ] [EMNLP, 2020] [Biomedical Event Extraction as Sequence Labeling](https://aclanthology.org/2020.emnlp-main.431)
125
+ - [ ] [EMNLP, 2020] [Introducing a New Dataset for Event Detection in Cybersecurity Texts](https://aclanthology.org/2020.emnlp-main.433)
126
+ - [ ] [EMNLP, 2020] [Affective Event Classification with Discourse-enhanced Self-training](https://aclanthology.org/2020.emnlp-main.452)
127
+ - [ ] [EMNLP, 2020] [Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction](https://aclanthology.org/2020.emnlp-main.461)
128
+ - [ ] [EMNLP, 2020] [Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction](https://aclanthology.org/2020.emnlp-main.461)
129
+ - [ ] [EMNLP, 2020] [Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction](https://aclanthology.org/2020.emnlp-main.690)
130
+ - [ ] [FINDINGS, 2020] [Syntactic and Semantic-driven Learning for Open Information Extraction](https://aclanthology.org/2020.findings-emnlp.69)
131
+ - [ ] [FINDINGS, 2020] [Event Extraction as Multi-turn Question Answering](https://aclanthology.org/2020.findings-emnlp.73)
132
+ - [ ] [FINDINGS, 2020] [Multiˆ2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT](https://aclanthology.org/2020.findings-emnlp.99)
133
+ - [ ] [FINDINGS, 2020] [Biomedical Event Extraction with Hierarchical Knowledge Graphs](https://aclanthology.org/2020.findings-emnlp.114)
134
+ - [ ] [FINDINGS, 2020] [Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning](https://aclanthology.org/2020.findings-emnlp.121)
135
+ - [ ] [FINDINGS, 2020] [Edge-Enhanced Graph Convolution Networks for Event Detection with Syntactic Relation](https://aclanthology.org/2020.findings-emnlp.211)
136
+ - [ ] [FINDINGS, 2020] [How Does Context Matter? On the Robustness of Event Detection with Context-Selective Mask Generalization](https://aclanthology.org/2020.findings-emnlp.229)
137
+ - [ ] [FINDINGS, 2020] [Resource-Enhanced Neural Model for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.318)
138
+ - [ ] [FINDINGS, 2020] [Resource-Enhanced Neural Model for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.318)
139
+ - [ ] [FINDINGS, 2020] [Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.326)
140
+ - [ ] [FINDINGS, 2020] [Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction](https://aclanthology.org/2020.findings-emnlp.326)
141
+ - [ ] [ACL, 2020] [The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain](https://aclanthology.org/2020.acl-main.116)
142
+ - [ ] [ACL, 2020] [Cross-media Structured Common Space for Multimedia Event Extraction](https://aclanthology.org/2020.acl-main.230)
143
+ - [ ] [ACL, 2020] [IMoJIE: Iterative Memory-Based Joint Open Information Extraction](https://aclanthology.org/2020.acl-main.521)
144
+ - [ ] [ACL, 2020] [Improving Event Detection via Open-domain Trigger Knowledge](https://aclanthology.org/2020.acl-main.522)
145
+ - [ ] [ACL, 2020] [Representation Learning for Information Extraction from Form-like Documents](https://aclanthology.org/2020.acl-main.580)
146
+ - [ ] [ACL, 2020] [A Two-Step Approach for Implicit Event Argument Detection](https://aclanthology.org/2020.acl-main.667)
147
+ - [ ] [ACL, 2020] [SciREX: A Challenge Dataset for Document-Level Information Extraction](https://aclanthology.org/2020.acl-main.670)
148
+ - [ ] [ACL, 2020] [A Joint Neural Model for Information Extraction with Global Features](https://aclanthology.org/2020.acl-main.713)
149
+ - [ ] [ACL, 2020] [Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding](https://aclanthology.org/2020.acl-main.714)
150
+ - [ ] [ACL, 2020] [Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web](https://aclanthology.org/2020.acl-tutorials.6)
151
+ - [ ] [EMNLP, 2019] [Open Event Extraction from Online Text using a Generative Adversarial Network](https://aclanthology.org/D19-1027)
152
+ - [ ] [EMNLP, 2019] [Cross-lingual Structure Transfer for Relation and Event Extraction](https://aclanthology.org/D19-1030)
153
+ - [ ] [EMNLP, 2019] [Cross-lingual Structure Transfer for Relation and Event Extraction](https://aclanthology.org/D19-1030)
154
+ - [ ] [EMNLP, 2019] [Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction](https://aclanthology.org/D19-1032)
155
+ - [ ] [EMNLP, 2019] [Event Detection with Trigger-Aware Lattice Neural Network](https://aclanthology.org/D19-1033)
156
+ - [ ] [EMNLP, 2019] [Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction](https://aclanthology.org/D19-1041)
157
+ - [ ] [EMNLP, 2019] [Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction](https://aclanthology.org/D19-1041)
158
+ - [ ] [EMNLP, 2019] [Supervising Unsupervised Open Information Extraction Models](https://aclanthology.org/D19-1067)
159
+ - [ ] [EMNLP, 2019] [Neural Cross-Lingual Event Detection with Minimal Parallel Resources](https://aclanthology.org/D19-1068)
160
+ - [ ] [EMNLP, 2019] [A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection](https://aclanthology.org/D19-1381)
161
+ - [ ] [EMNLP, 2019] [Reporting the Unreported: Event Extraction for Analyzing the Local Representation of Hate Crimes](https://aclanthology.org/D19-1580)
162
+ - [ ] [EMNLP, 2019] [Event Detection with Multi-Order Graph Convolution and Aggregated Attention](https://aclanthology.org/D19-1582)
163
+ - [ ] [EMNLP, 2019] [Coverage of Information Extraction from Sentences and Paragraphs](https://aclanthology.org/D19-1583)
164
+ - [ ] [EMNLP, 2019] [HMEAE: Hierarchical Modular Event Argument Extraction](https://aclanthology.org/D19-1584)
165
+ - [ ] [EMNLP, 2019] [HMEAE: Hierarchical Modular Event Argument Extraction](https://aclanthology.org/D19-1584)
166
+ - [ ] [EMNLP, 2019] [Entity, Relation, and Event Extraction with Contextualized Span Representations](https://aclanthology.org/D19-1585)
167
+ - [ ] [ACL, 2019] [Unsupervised Information Extraction: Regularizing Discriminative Approaches with Relation Distribution Losses](https://aclanthology.org/P19-1133)
168
+ - [ ] [ACL, 2019] [Open Domain Event Extraction Using Neural Latent Variable Models](https://aclanthology.org/P19-1276)
169
+ - [ ] [ACL, 2019] [Literary Event Detection](https://aclanthology.org/P19-1353)
170
+ - [ ] [ACL, 2019] [Distilling Discrimination and Generalization Knowledge for Event Detection via Delta-Representation Learning](https://aclanthology.org/P19-1429)
171
+ - [ ] [ACL, 2019] [Cost-sensitive Regularization for Label Confusion-aware Event Detection](https://aclanthology.org/P19-1521)
172
+ - [ ] [ACL, 2019] [Exploring Pre-trained Language Models for Event Extraction and Generation](https://aclanthology.org/P19-1522)
173
+ - [ ] [ACL, 2019] [Improving Open Information Extraction via Iterative Rank-Aware Learning](https://aclanthology.org/P19-1523)
174
+ - [ ] [ACL, 2019] [Rapid Customization for Event Extraction](https://aclanthology.org/P19-3006)
175
+ - [ ] [NAACL, 2019] [Event Detection without Triggers](https://aclanthology.org/N19-1080)
176
+ - [ ] [NAACL, 2019] [GraphIE: A Graph-Based Framework for Information Extraction](https://aclanthology.org/N19-1082)
177
+ - [ ] [NAACL, 2019] [OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference](https://aclanthology.org/N19-1083)
178
+ - [ ] [NAACL, 2019] [Adversarial Training for Weakly Supervised Event Detection](https://aclanthology.org/N19-1105)
179
+ - [ ] [NAACL, 2019] [Biomedical Event Extraction based on Knowledge-driven Tree-LSTM](https://aclanthology.org/N19-1145)
180
+ - [ ] [NAACL, 2019] [Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction](https://aclanthology.org/N19-1150)
181
+ - [ ] [NAACL, 2019] [Open Information Extraction from Question-Answer Pairs](https://aclanthology.org/N19-1239)
182
+ - [ ] [NAACL, 2019] [A general framework for information extraction using dynamic span graphs](https://aclanthology.org/N19-1308)
183
+ - [ ] [NAACL, 2019] [OpenCeres: When Open Information Extraction Meets the Semi-Structured Web](https://aclanthology.org/N19-1309)
184
+ - [ ] [NAACL, 2019] [Graph Convolution for Multimodal Information Extraction from Visually Rich Documents](https://aclanthology.org/N19-2005)
185
+ - [ ] [NAACL, 2019] [TOI-CNN: a Solution of Information Extraction on Chinese Insurance Policy](https://aclanthology.org/N19-2022)
186
+ - [ ] [NAACL, 2019] [SEDTWik: Segmentation-based Event Detection from Tweets Using Wikipedia](https://aclanthology.org/N19-3011)
187
+ - [ ] [NAACL, 2019] [Multilingual Entity, Relation, Event and Human Value Extraction](https://aclanthology.org/N19-4019)
188
+ - [ ] [NAACL, 2019] [Browsing Health: Information Extraction to Support New Interfaces for Accessing Medical Evidence](https://aclanthology.org/W19-2606)
189
+ - [ ] [CL, 2019] [Novel Event Detection and Classification for Historical Texts](https://aclanthology.org/J19-2002)
190
+ - [ ] [CL, 2019] [Novel Event Detection and Classification for Historical Texts](https://aclanthology.org/J19-2002)
191
+ - [ ] [TACL, 2018] [Event Time Extraction with a Decision Tree of Neural Classifiers](https://aclanthology.org/Q18-1006)
192
+ - [ ] [EMNLP, 2018] [Event Detection with Neural Networks: A Rigorous Empirical Evaluation](https://aclanthology.org/D18-1122)
193
+ - [ ] [EMNLP, 2018] [Exploiting Contextual Information via Dynamic Memory Network for Event Detection](https://aclanthology.org/D18-1127)
194
+ - [ ] [EMNLP, 2018] [Temporal Information Extraction by Predicting Relative Time-lines](https://aclanthology.org/D18-1155)
195
+ - [ ] [EMNLP, 2018] [Collective Event Detection via a Hierarchical and Bias Tagging Networks with Gated Multi-level Attention Mechanisms](https://aclanthology.org/D18-1158)
196
+ - [ ] [EMNLP, 2018] [Visual Supervision in Bootstrapped Information Extraction](https://aclanthology.org/D18-1229)
197
+ - [ ] [EMNLP, 2018] [Similar but not the Same: Word Sense Disambiguation Improves Event Detection via Neural Representation Matching](https://aclanthology.org/D18-1517)
198
+ - [ ] [CL, 2018] [Last Words: What Can Be Accomplished with the State of the Art in Information Extraction? A Personal View](https://aclanthology.org/J18-4004)
199
+ - [ ] [EMNLP, 2018] [A Multilingual Information Extraction Pipeline for Investigative Journalism](https://aclanthology.org/D18-2014)
200
+ - [ ] [EMNLP, 2018] [Joint Modeling for Query Expansion and Information Extraction with Reinforcement Learning](https://aclanthology.org/W18-5506)
201
+ - [ ] [COLING, 2018] [Low-resource Cross-lingual Event Type Detection via Distant Supervision with Minimal Effort](https://aclanthology.org/C18-1007)
202
+ - [ ] [COLING, 2018] [Open-Domain Event Detection using Distant Supervision](https://aclanthology.org/C18-1075)
203
+ - [ ] [COLING, 2018] [Open Information Extraction from Conjunctive Sentences](https://aclanthology.org/C18-1194)
204
+ - [ ] [COLING, 2018] [Graphene: Semantically-Linked Propositions in Open Information Extraction](https://aclanthology.org/C18-1195)
205
+ - [ ] [COLING, 2018] [Open Information Extraction on Scientific Text: An Evaluation](https://aclanthology.org/C18-1289)
206
+ - [ ] [COLING, 2018] [A Survey on Open Information Extraction](https://aclanthology.org/C18-1326)
207
+ - [ ] [COLING, 2018] [Graphene: a Context-Preserving Open Information Extraction System](https://aclanthology.org/C18-2021)
208
+ - [ ] [ACL, 2018] [Self-regulation: Employing a Generative Adversarial Network to Improve Event Detection](https://aclanthology.org/P18-1048)
209
+ - [ ] [ACL, 2018] [Context-Aware Neural Model for Temporal Information Extraction](https://aclanthology.org/P18-1049)
210
+ - [ ] [ACL, 2018] [Adaptive Scaling for Sparse Detection in Information Extraction](https://aclanthology.org/P18-1095)
211
+ - [ ] [ACL, 2018] [Nugget Proposal Networks for Chinese Event Detection](https://aclanthology.org/P18-1145)
212
+ - [ ] [ACL, 2018] [Zero-Shot Transfer Learning for Event Extraction](https://aclanthology.org/P18-1201)
213
+ - [ ] [ACL, 2018] [Neural Open Information Extraction](https://aclanthology.org/P18-2065)
214
+ - [ ] [ACL, 2018] [Document Embedding Enhanced Event Detection with Hierarchical and Supervised Attention](https://aclanthology.org/P18-2066)
215
+ - [ ] [ACL, 2018] [DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data](https://aclanthology.org/P18-4009)
216
+ - [ ] [ACL, 2018] [Economic Event Detection in Company-Specific News Text](https://aclanthology.org/W18-3101)
217
+ - [ ] [NAACL, 2018] [Supervised Open Information Extraction](https://aclanthology.org/N18-1081)
218
+ - [ ] [NAACL, 2018] [Keep Your Bearings: Lightly-Supervised Information Extraction with Ladder Networks That Avoids Semantic Drift](https://aclanthology.org/N18-2057)
219
+ - [ ] [NAACL, 2018] [Semi-Supervised Event Extraction with Paraphrase Clusters](https://aclanthology.org/N18-2058)
220
+ - [ ] [NAACL, 2018] [Syntactic Patterns Improve Information Extraction for Medical Search](https://aclanthology.org/N18-2060)
221
+ - [ ] [EMNLP, 2017] [Temporal Information Extraction for Question Answering Using Syntactic Dependencies in an LSTM-based Architecture](https://aclanthology.org/D17-1092)
222
+ - [ ] [EMNLP, 2017] [MinIE: Minimizing Facts in Open Information Extraction](https://aclanthology.org/D17-1278)
223
+ - [ ] [EMNLP, 2017] [Scientific Information Extraction with Semi-supervised Neural Tagging](https://aclanthology.org/D17-1279)
224
+ - [ ] [EMNLP, 2017] [Speeding up Reinforcement Learning-based Information Extraction Training using Asynchronous Methods](https://aclanthology.org/D17-1281)
225
+ - [ ] [ACL, 2017] [Automatically Labeled Data Generation for Large Scale Event Extraction](https://aclanthology.org/P17-1038)
226
+ - [ ] [ACL, 2017] [Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms](https://aclanthology.org/P17-1164)
227
+ - [ ] [ACL, 2017] [English Event Detection With Translated Language Features](https://aclanthology.org/P17-2046)
228
+ - [ ] [ACL, 2017] [Answering Complex Questions Using Open Information Extraction](https://aclanthology.org/P17-2049)
229
+ - [ ] [COLING, 2016] [Leveraging Multilingual Training for Limited Resource Event Extraction](https://aclanthology.org/C16-1114)
230
+ - [ ] [COLING, 2016] [Incremental Global Event Extraction](https://aclanthology.org/C16-1215)
231
+ - [ ] [COLING, 2016] [Event Detection with Burst Information Networks](https://aclanthology.org/C16-1309)
232
+ - [ ] [COLING, 2016] [Video Event Detection by Exploiting Word Dependencies from Image Captions](https://aclanthology.org/C16-1313)
233
+ - [ ] [COLING, 2016] [OCR++: A Robust Framework For Information Extraction from Scholarly Articles](https://aclanthology.org/C16-1320)
234
+ - [ ] [COLING, 2016] [Multilingual Information Extraction with PolyglotIE](https://aclanthology.org/C16-2056)
235
+ - [ ] [EMNLP, 2016] [Nested Propositions in Open Information Extraction](https://aclanthology.org/D16-1006)
236
+ - [ ] [EMNLP, 2016] [Event Detection and Co-reference with Minimal Supervision](https://aclanthology.org/D16-1038)
237
+ - [ ] [EMNLP, 2016] [Modeling Skip-Grams for Event Detection with Convolutional Neural Networks](https://aclanthology.org/D16-1085)
238
+ - [ ] [EMNLP, 2016] [Porting an Open Information Extraction System from English to German](https://aclanthology.org/D16-1086)
239
+ - [ ] [EMNLP, 2016] [Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities](https://aclanthology.org/D16-1152)
240
+ - [ ] [EMNLP, 2016] [Creating a Large Benchmark for Open Information Extraction](https://aclanthology.org/D16-1252)
241
+ - [ ] [EMNLP, 2016] [Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning](https://aclanthology.org/D16-1261)
242
+ - [ ] [ACL, 2016] [Liberal Event Extraction and Event Schema Induction](https://aclanthology.org/P16-1025)
243
+ - [ ] [ACL, 2016] [Jointly Event Extraction and Visualization on Twitter via Probabilistic Modelling](https://aclanthology.org/P16-1026)
244
+ - [ ] [ACL, 2016] [RBPB: Regularization-Based Pattern Balancing Method for Event Extraction](https://aclanthology.org/P16-1116)
245
+ - [ ] [ACL, 2016] [Leveraging FrameNet to Improve Automatic Event Detection](https://aclanthology.org/P16-1201)
246
+ - [ ] [ACL, 2016] [A Language-Independent Neural Network for Event Detection](https://aclanthology.org/P16-2011)
247
+ - [ ] [ACL, 2016] [Event Nugget Detection with Forward-Backward Recurrent Neural Networks](https://aclanthology.org/P16-2060)
248
+ - [ ] [ACL, 2016] [new/s/leak – Information Extraction and Visualization for Investigative Data Journalists](https://aclanthology.org/P16-4028)
249
+ - [ ] [NAACL, 2016] [Joint Event Extraction via Recurrent Neural Networks](https://aclanthology.org/N16-1034)
250
+ - [ ] [NAACL, 2016] [Expectation-Regulated Neural Model for Event Mention Extraction](https://aclanthology.org/N16-1045)
251
+ - [ ] [NAACL, 2016] [Bidirectional RNN for Medical Event Detection in Electronic Health Records](https://aclanthology.org/N16-1056)
252
+ - [ ] [NAACL, 2016] [Cross-genre Event Extraction with Knowledge Enrichment](https://aclanthology.org/N16-1137)
253
+ - [ ] [NAACL, 2016] [Cross-media Event Extraction and Recommendation](https://aclanthology.org/N16-3015)
254
+ - [ ] [NAACL, 2015] [Diamonds in the Rough: Event Extraction from Imperfect Microblog Data](https://aclanthology.org/N15-1066)
255
+ - [ ] [TACL, 2015] [Exploiting Parallel News Streams for Unsupervised Event Extraction](https://aclanthology.org/Q15-1009)
256
+ - [ ] [TACL, 2015] [Large-Scale Information Extraction from Textual Definitions through Deep Syntactic and Semantic Analysis](https://aclanthology.org/Q15-1038)
257
+ - [ ] [EMNLP, 2015] [Improving Distant Supervision for Information Extraction Using Label Propagation Through Lists](https://aclanthology.org/D15-1060)
258
+ - [ ] [EMNLP, 2015] [Inferring Binary Relation Schemas for Open Information Extraction](https://aclanthology.org/D15-1065)
259
+ - [ ] [EMNLP, 2015] [Event Detection and Factuality Assessment with Non-Expert Supervision](https://aclanthology.org/D15-1189)
260
+ - [ ] [EMNLP, 2015] [Abstractive Multi-document Summarization with Semantic Information Extraction](https://aclanthology.org/D15-1219)
261
+ - [ ] [EMNLP, 2015] [Twitter-scale New Event Detection via K-term Hashing](https://aclanthology.org/D15-1310)
262
+ - [ ] [EMNLP, 2015] [Transparent Machine Learning for Information Extraction: State-of-the-Art and the Future](https://aclanthology.org/D15-2003)
263
+ - [ ] [ACL, 2015] [Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks](https://aclanthology.org/P15-1017)
264
+ - [ ] [ACL, 2015] [Leveraging Linguistic Structure For Open Domain Information Extraction](https://aclanthology.org/P15-1034)
265
+ - [ ] [ACL, 2015] [Joint Information Extraction and Reasoning: A Scalable Statistical Relational Learning Approach](https://aclanthology.org/P15-1035)
266
+ - [ ] [ACL, 2015] [A Lexicalized Tree Kernel for Open Information Extraction](https://aclanthology.org/P15-2046)
267
+ - [ ] [ACL, 2015] [Event Detection and Domain Adaptation with Convolutional Neural Networks](https://aclanthology.org/P15-2060)
268
+ - [ ] [ACL, 2015] [Disease Event Detection based on Deep Modality Analysis](https://aclanthology.org/P15-3005)
269
+ - [ ] [ACL, 2015] [A Domain-independent Rule-based Framework for Event Extraction](https://aclanthology.org/P15-4022)
270
+ - [ ] [NAACL, 2015] [Exploring Relational Features and Learning under Distant Supervision for Information Extraction Tasks](https://aclanthology.org/N15-2006)
271
+ - [ ] [NAACL, 2015] [ICE: Rapid Information Extraction Customization for NLP Novices](https://aclanthology.org/N15-3007)
272
+ - [ ] [EMNLP, 2014] [Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features](https://aclanthology.org/D14-1090)
273
+ - [ ] [EMNLP, 2014] [Exploiting Community Emotion for Microblog Event Detection](https://aclanthology.org/D14-1123)
274
+ - [ ] [EMNLP, 2014] [Event Role Extraction using Domain-Relevant Word Representations](https://aclanthology.org/D14-1199)
275
+ - [ ] [EMNLP, 2014] [Combining Visual and Textual Features for Information Extraction from Online Flyers](https://aclanthology.org/D14-1206)
276
+ - [ ] [EMNLP, 2014] [Major Life Event Extraction from Twitter based on Congratulations/Condolences Speech Acts](https://aclanthology.org/D14-1214)
277
+ - [ ] [COLING, 2014] [Employing Event Inference to Improve Semi-Supervised Chinese Event Extraction](https://aclanthology.org/C14-1204)
278
+ - [ ] [COLING, 2014] [Comparable Study of Event Extraction in Newswire and Biomedical Domains](https://aclanthology.org/C14-1214)
279
+ - [ ] [ACL, 2014] [Information Extraction over Structured Data: Question Answering with Freebase](https://aclanthology.org/P14-1090)
280
+ - [ ] [ACL, 2014] [A Simple Bayesian Modelling Approach to Event Extraction from Twitter](https://aclanthology.org/P14-2114)
281
+ - [ ] [ACL, 2014] [Open Information Extraction for Spanish Language based on Syntactic Constraints](https://aclanthology.org/P14-3011)
282
+ - [ ] [TACL, 2013] [Modeling Missing Data in Distant Supervision for Information Extraction](https://aclanthology.org/Q13-1030)
283
+ - [ ] [EMNLP, 2013] [Rule-Based Information Extraction is Dead! Long Live Rule-Based Information Extraction Systems!](https://aclanthology.org/D13-1079)
284
+ - [ ] [ACL, 2013] [Joint Event Extraction via Structured Prediction with Global Features](https://aclanthology.org/P13-1008)
285
+ - [ ] [ACL, 2013] [Argument Inference from Relevant Event Mentions in Chinese Argument Extraction](https://aclanthology.org/P13-1145)
286
+ - [ ] [ACL, 2013] [Argument Inference from Relevant Event Mentions in Chinese Argument Extraction](https://aclanthology.org/P13-1145)
287
+ - [ ] [ACL, 2013] [Propminer: A Workflow for Interactive Information Extraction and Exploration using Dependency Trees](https://aclanthology.org/P13-4027)
288
+ - [ ] [NAACL, 2013] [Open Information Extraction with Tree Kernels](https://aclanthology.org/N13-1107)
289
+ - [ ] [COLING, 2012] [Joint Modeling for Chinese Event Extraction with Rich Linguistic Features](https://aclanthology.org/C12-1033)
290
+ - [ ] [COLING, 2012] [Employing Morphological Structures and Sememes for Chinese Event Extraction](https://aclanthology.org/C12-1099)
291
+ - [ ] [COLING, 2012] [Joint Modeling of Trigger Identification and Event Type Determination in Chinese Event Extraction](https://aclanthology.org/C12-1100)
292
+ - [ ] [COLING, 2012] [ISO-TimeML Event Extraction in Persian Text](https://aclanthology.org/C12-1179)
293
+ - [ ] [COLING, 2012] [Parenthetical Classification for Information Extraction](https://aclanthology.org/C12-2030)
294
+ - [ ] [COLING, 2012] [Sourcing the Crowd for a Few Good Ones: Event Type Detection](https://aclanthology.org/C12-2121)
295
+ - [ ] [COLING, 2012] [Optimal Scheduling of Information Extraction Algorithms](https://aclanthology.org/C12-2125)
296
+ - [ ] [COLING, 2012] [Open Information Extraction for SOV Language Based on Entity-Predicate Pair Detection](https://aclanthology.org/C12-3038)
297
+ - [ ] [COLING, 2012] [Markov Chains for Robust Graph-Based Commonsense Information Extraction](https://aclanthology.org/C12-3055)
298
+ - [ ] [ACL, 2012] [Automatic Event Extraction with Structured Preference Modeling](https://aclanthology.org/P12-1088)
299
+ - [ ] [ACL, 2012] [A Novel Burst-based Text Representation Model for Scalable Event Detection](https://aclanthology.org/P12-2009)
300
+ - [ ] [ACL, 2012] [ACCURAT Toolkit for Multi-Level Alignment and Information Extraction from Comparable Corpora](https://aclanthology.org/P12-3016)
301
+ - [ ] [ACL, 2012] [WizIE: A Best Practices Guided Development Environment for Information Extraction](https://aclanthology.org/P12-3019)
302
+ - [ ] [EMNLP, 2012] [Open Language Learning for Information Extraction](https://aclanthology.org/D12-1048)
303
+ - [ ] [EMNLP, 2012] [Employing Compositional Semantics and Discourse Consistency in Chinese Event Extraction](https://aclanthology.org/D12-1092)
304
+ - [ ] [EMNLP, 2012] [Building a Lightweight Semantic Model for Unsupervised Information Extraction on Short Listings](https://aclanthology.org/D12-1099)
305
+ - [ ] [NAACL, 2012] [A Weighting Scheme for Open Information Extraction](https://aclanthology.org/N12-2011)
306
+ - [ ] [EMNLP, 2011] [Fast and Robust Joint Models for Biomedical Event Extraction](https://aclanthology.org/D11-1001)
307
+ - [ ] [EMNLP, 2011] [Unsupervised Information Extraction with Distributional Prior Knowledge](https://aclanthology.org/D11-1075)
308
+ - [ ] [EMNLP, 2011] [Identifying Relations for Open Information Extraction](https://aclanthology.org/D11-1142)
309
+ - [ ] [ACL, 2011] [Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations](https://aclanthology.org/P11-1055)
310
+ - [ ] [ACL, 2011] [Template-Based Information Extraction without the Templates](https://aclanthology.org/P11-1098)
311
+ - [ ] [ACL, 2011] [Using Cross-Entity Inference to Improve Event Extraction](https://aclanthology.org/P11-1113)
312
+ - [ ] [ACL, 2011] [Event Extraction as Dependency Parsing](https://aclanthology.org/P11-1163)
313
+ - [ ] [ACL, 2011] [Can Document Selection Help Semi-supervised Learning? A Case Study On Event Extraction](https://aclanthology.org/P11-2045)
314
+ - [ ] [ACL, 2011] [SystemT: A Declarative Information Extraction System](https://aclanthology.org/P11-4019)
315
+ - [ ] [EMNLP, 2010] [Evaluating the Impact of Alternative Dependency Graph Encodings on Solving Event Extraction Tasks](https://aclanthology.org/D10-1096)
316
+ - [ ] [COLING, 2010] [Automatic Detection of Non-deverbal Event Nouns for Quick Lexicon Production](https://aclanthology.org/C10-1006)
317
+ - [ ] [COLING, 2010] [Filtered Ranking for Bootstrapping in Event Extraction](https://aclanthology.org/C10-1077)
318
+ - [ ] [COLING, 2010] [Evaluating Dependency Representations for Event Extraction](https://aclanthology.org/C10-1088)
319
+ - [ ] [COLING, 2010] [Challenges from Information Extraction to Information Fusion](https://aclanthology.org/C10-2058)
320
+ - [ ] [COLING, 2010] [Enhancing Multi-lingual Information Extraction via Cross-Media Inference and Fusion](https://aclanthology.org/C10-2072)
321
+ - [ ] [COLING, 2010] [“Expresses-an-opinion-about”: using corpus statistics in an information extraction approach to opinion mining](https://aclanthology.org/C10-2126)
322
+ - [ ] [COLING, 2010] [Shallow Information Extraction from Medical Forum Data](https://aclanthology.org/C10-2133)
323
+ - [ ] [ACL, 2010] [Open Information Extraction Using Wikipedia](https://aclanthology.org/P10-1013)
324
+ - [ ] [ACL, 2010] [SystemT: An Algebraic Approach to Declarative Information Extraction](https://aclanthology.org/P10-1014)
325
+ - [ ] [ACL, 2010] [Using Document Level Cross-Event Inference to Improve Event Extraction](https://aclanthology.org/P10-1081)
326
+ - [ ] [ACL, 2010] [An Entity-Level Approach to Information Extraction](https://aclanthology.org/P10-2054)
327
+ - [ ] [NAACL, 2010] [Utility Evaluation of Cross-document Information Extraction](https://aclanthology.org/N10-1036)
328
+ - [ ] [NAACL, 2010] [Constraint-Driven Rank-Based Learning for Information Extraction](https://aclanthology.org/N10-1111)
329
+ - [ ] [EMNLP, 2009] [A Unified Model of Phrasal and Sentential Evidence for Information Extraction](https://aclanthology.org/D09-1016)
330
+ - [ ] [ACL, 2009] [Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm](https://aclanthology.org/P09-1061)
331
+ - [ ] [ACL, 2009] [Mining Association Language Patterns for Negative Life Event Classification](https://aclanthology.org/P09-2051)
332
+ - [ ] [NAACL, 2009] [A Local Tree Alignment-based Soft Pattern Matching Approach for Information Extraction](https://aclanthology.org/N09-2043)
333
+ - [ ] [NAACL, 2009] [Language Specific Issue and Feature Exploration in Chinese Event Extraction](https://aclanthology.org/N09-2053)
334
+ - [ ] [NAACL, 2009] [Solving the “Who’s Mark Johnson Puzzle”: Information Extraction Based Cross Document Coreference](https://aclanthology.org/N09-3002)
335
+ - [ ] [CL, 2008] [Book Reviews: Information Extraction: Algorithms and Prospects in a Retrieval Context by Marie-Francine Moens](https://aclanthology.org/J08-2008)
336
+ - [ ] [EMNLP, 2008] [Regular Expression Learning for Information Extraction](https://aclanthology.org/D08-1003)
337
+ - [ ] [COLING, 2008] [Investigating Statistical Techniques for Sentence-Level Event Classification](https://aclanthology.org/C08-1078)
338
+ - [ ] [COLING, 2008] [Event Frame Extraction Based on a Gene Regulation Corpus](https://aclanthology.org/C08-1096)
339
+ - [ ] [ACL, 2008] [Refining Event Extraction through Cross-Document Inference](https://aclanthology.org/P08-1030)
340
+ - [ ] [EMNLP, 2007] [Effective Information Extraction with Semantic Affinity Patterns and Relevant Regions](https://aclanthology.org/D07-1075)
341
+ - [ ] [EMNLP, 2007] [Bootstrapping Information Extraction from Field Books](https://aclanthology.org/D07-1087)
342
+ - [ ] [ACL, 2007] [A Multi-resolution Framework for Information Extraction from Free Text](https://aclanthology.org/P07-1075)
343
+ - [ ] [ACL, 2007] [Sparse Information Extraction: Unsupervised Language Models to the Rescue](https://aclanthology.org/P07-1088)
344
+ - [ ] [ACL, 2007] [System Demonstration of On-Demand Information Extraction](https://aclanthology.org/P07-2005)
345
+ - [ ] [NAACL, 2007] [Question Answering Using Integrated Information Retrieval and Information Extraction](https://aclanthology.org/N07-1067)
346
+ - [ ] [NAACL, 2007] [A High Accuracy Method for Semi-Supervised Information Extraction](https://aclanthology.org/N07-2043)
347
+ - [ ] [NAACL, 2007] [TextRunner: Open Information Extraction on the Web](https://aclanthology.org/N07-4013)
348
+ - [ ] [EMNLP, 2006] [Automatic Construction of Predicate-argument Structure Patterns for Biomedical Information Extraction](https://aclanthology.org/W06-1634)
349
+ - [ ] [EMNLP, 2006] [Unsupervised Information Extraction Approach Using Graph Mutual Reinforcement](https://aclanthology.org/W06-1659)
350
+ - [ ] [EMNLP, 2006] [Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger](https://aclanthology.org/W06-1670)
351
+ - [ ] [COLING, 2006] [Segment-Based Hidden Markov Models for Information Extraction](https://aclanthology.org/P06-1061)
352
+ - [ ] [COLING, 2006] [Event Extraction in a Plot Advice Agent](https://aclanthology.org/P06-1108)
353
+ - [ ] [COLING, 2006] [ARE: Instance Splitting Strategies for Dependency Relation-Based Information Extraction](https://aclanthology.org/P06-2074)
354
+ - [ ] [COLING, 2006] [On-Demand Information Extraction](https://aclanthology.org/P06-2094)
355
+ - [ ] [NAACL, 2006] [Preemptive Information Extraction using Unrestricted Relation Discovery](https://aclanthology.org/N06-1039)
356
+ - [ ] [NAACL, 2006] [A Comparison of Tagging Strategies for Statistical Information Extraction](https://aclanthology.org/N06-2038)
357
+ - [ ] [ACL, 2005] [Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling](https://aclanthology.org/P05-1045)
358
+ - [ ] [ACL, 2005] [Unsupervised Learning of Field Segmentation Models for Information Extraction](https://aclanthology.org/P05-1046)
359
+ - [ ] [ACL, 2005] [Multi-Field Information Extraction and Cross-Document Fusion](https://aclanthology.org/P05-1060)
360
+ - [ ] [ACL, 2005] [Resume Information Extraction with Cascaded Hybrid Model](https://aclanthology.org/P05-1062)
361
+ - [ ] [COLING, 2004] [Cascading Use of Soft and Hard Matching Pattern Rules for Weakly Supervised Information Extraction](https://aclanthology.org/C04-1078)
362
+ - [ ] [COLING, 2004] [Information Extraction from Single and Multiple Sentences](https://aclanthology.org/C04-1126)
363
+ - [ ] [COLING, 2004] [Cross-lingual Information Extraction System Evaluation](https://aclanthology.org/C04-1127)
364
+ - [ ] [COLING, 2004] [Information Extraction for Question Answering: Improving Recall Through Syntactic Patterns](https://aclanthology.org/C04-1188)
365
+ - [ ] [NAACL, 2004] [Accurate Information Extraction from Research Papers using Conditional Random Fields](https://aclanthology.org/N04-1042)
366
+ - [ ] [NAACL, 2004] [Confidence Estimation for Information Extraction](https://aclanthology.org/N04-4028)
367
+ - [ ] [ACL, 2004] [Mining Metalinguistic Activity in Corpora to Create Lexical Resources Using Information Extraction Techniques: the MOP System](https://aclanthology.org/P04-1028)
368
+ - [ ] [ACL, 2004] [Collective Information Extraction with Relational Markov Networks](https://aclanthology.org/P04-1056)
369
+ - [ ] [ACL, 2004] [Weakly Supervised Learning for Cross-document Person Name Disambiguation Supported by Information Extraction](https://aclanthology.org/P04-1076)
370
+ - [ ] [ACL, 2004] [Combining Lexical, Syntactic, and Semantic Features with Maximum Entropy Models for Information Extraction](https://aclanthology.org/P04-3022)
371
+ - [ ] [NAACL, 2003] [Story Link Detection and New Event Detection are Asymmetric](https://aclanthology.org/N03-2005)
372
+ - [ ] [NAACL, 2003] [pre-CODIE–Crosslingual On-Demand Information Extraction](https://aclanthology.org/N03-4013)
373
+ - [ ] [ACL, 2003] [Using Predicate-Argument Structures for Information Extraction](https://aclanthology.org/P03-1002)
374
+ - [ ] [ACL, 2003] [Closing the Gap: Learning-Based Information Extraction Rivaling Knowledge-Engineering Methods](https://aclanthology.org/P03-1028)
375
+ - [ ] [ACL, 2003] [Optimizing Story Link Detection is not Equivalent to Optimizing New Event Detection](https://aclanthology.org/P03-1030)
376
+ - [ ] [ACL, 2003] [Integrating Information Extraction and Automatic Hyperlinking](https://aclanthology.org/P03-2019)
377
+ - [ ] [COLING, 2002] [Inducing Information Extraction Systems for New Languages via Cross-language Projection](https://aclanthology.org/C02-1070)
378
+ - [ ] [COLING, 2002] [Location Normalization for Information Extraction](https://aclanthology.org/C02-1127)
379
+ - [ ] [COLING, 2002] [Semantic Case Role Detection for Information Extraction](https://aclanthology.org/C02-2011)
380
+ - [ ] [EMNLP, 2002] [Information Extraction from Voicemail Transcripts](https://aclanthology.org/W02-1041)
381
+ - [ ] [EMNLP, 2001] [Information Extraction Using the Structured Language Model](https://aclanthology.org/W01-0510)
382
+ - [ ] [ACL, 2001] [Information Extraction from Voicemail](https://aclanthology.org/P01-1039)
383
+ - [ ] [COLING, 2000] [Learning Semantic-Level Information Extraction Rules by Type-Oriented ILP](https://aclanthology.org/C00-2101)
384
+ - [ ] [COLING, 2000] [Automatic Acquisition of Domain Knowledge for Information Extraction](https://aclanthology.org/C00-2136)
385
+ - [ ] [COLING, 2000] [The Week at a Glance - Cross-language Cross-document Information Extraction and Translation](https://aclanthology.org/C00-2147)
386
+ - [ ] [ACL, 2000] [Invited Talk: Generic NLP Technologies: Language, Knowledge and Information Extraction](https://aclanthology.org/P00-1002)
387
+ - [ ] [ACL, 2000] [From Information Retrieval to Information Extraction](https://aclanthology.org/W00-1109)
388
+ - [ ] [ACL, 1999] [Automatic Speech Recognition and Its Application to Information Extraction](https://aclanthology.org/P99-1002)
389
+ - [ ] [COLING, 1998] [Toward General-Purpose Learning for Information Extraction](https://aclanthology.org/C98-1064)
390
+ - [ ] [ACL, 1998] [Toward General-Purpose Learning for Information Extraction](https://aclanthology.org/P98-1067)
391
+ - [ ] [EMNLP, 1997] [Probabilistic Coreference in Information Extraction](https://aclanthology.org/W97-0319)
392
+ - [ ] [ACL, 1995] [Constraint-Based Event Recognition for Information Extraction](https://aclanthology.org/P95-1042)
393
+ - [ ] [ACL, 1995] [Constraint-Based Event Recognition for Information Extraction](https://aclanthology.org/P95-1042)
394
+ - [ ] [COLING, 1994] [Pattern Matching in the TEXTRACT Information Extraction System](https://aclanthology.org/C94-2173)
395
+ - [ ] [CL, 1993] [Book Reviews:Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval](https://aclanthology.org/J93-1012)
396
+ - [ ] [COLING, 1990] [Information Extraction and Semantic Constraints](https://aclanthology.org/C90-3071)
run.py ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from src.interfaces.aclanthology import AclanthologyPaperList
2
+ from src.utils import dump_paper_list_to_markdown_checklist
3
+
4
+ if __name__ == "__main__":
5
+ # use `bash scripts/get_aclanthology.sh` to download and prepare anthology data
6
+ paper_list = AclanthologyPaperList("cache/aclanthology.json")
7
+ ee_query = {
8
+ "title": [
9
+ ["information extraction"],
10
+ ["event", "extraction"],
11
+ ["event", "argument", "extraction"],
12
+ ["event", "detection"],
13
+ ["event", "classification"],
14
+ ["event", "tracking"],
15
+ ["event", "relation", "extraction"],
16
+ ],
17
+ "venue": [
18
+ ["acl"],
19
+ ["emnlp"],
20
+ ["naacl"],
21
+ ["coling"],
22
+ ["findings"],
23
+ ["tacl"],
24
+ ["cl"],
25
+ ],
26
+ }
27
+ ee_papers = paper_list.search(ee_query)
28
+ dump_paper_list_to_markdown_checklist(ee_papers, "results/ee-paper-list.md")
29
+
30
+ doc_query = {
31
+ "title": [
32
+ ["document-level"],
33
+ ],
34
+ "venue": [
35
+ ["acl"],
36
+ ["emnlp"],
37
+ ["naacl"],
38
+ ["coling"],
39
+ ["findings"],
40
+ ["tacl"],
41
+ ["cl"],
42
+ ],
43
+ }
44
+ doc_papers = paper_list.search(doc_query)
45
+ dump_paper_list_to_markdown_checklist(doc_papers, "results/doc-paper-list.md")
scripts/download_cache.py ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from src.utils import download
2
+
3
+ FILES = {
4
+ "aclanthology": "https://aclanthology.org/anthology+abstracts.bib.gz",
5
+ "dblp": "https://dblp.uni-trier.de/xml/dblp.xml.gz",
6
+ }
7
+
8
+
9
+ if __name__ == "__main__":
10
+ # download(FILES["aclanthology"], "./cache/anthology+abstracts.bib.gz")
11
+ download(FILES["dblp"], "./cache/dblp.xml.gz")
scripts/get_aclanthology.sh ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ mkdir cache
2
+ cd cache
3
+ if ! [ -f acl-anthology/bin/anthology/anthology.py ]; then
4
+ git clone https://github.com/acl-org/acl-anthology
5
+ else
6
+ cd acl-anthology
7
+ git pull
8
+ cd ..
9
+ fi
10
+ cd acl-anthology/bin
11
+
12
+ python -c '
13
+ import json
14
+ from anthology import Anthology
15
+
16
+ anthology = Anthology(importdir="../data")
17
+ pops = ["xml_booktitle", "xml_title", "xml_url", "xml_abstract"]
18
+ papers = []
19
+ for paper in anthology.papers.values():
20
+ p = paper.as_dict()
21
+ if "xml_abstract" in p:
22
+ p["abstract"] = paper.get_abstract(form="latex")
23
+ for popkey in pops:
24
+ if popkey in p:
25
+ p.pop(popkey)
26
+ if "author" in p:
27
+ p["author"] = [a[0].as_dict() for a in p["author"]]
28
+ if "editor" in p:
29
+ p["editor"] = [a[0].as_dict() for a in p["editor"]]
30
+ papers.append(p)
31
+
32
+ with open("../../aclanthology.json", "wt", encoding="utf8") as fout:
33
+ json.dump(papers, fout, ensure_ascii=False)
34
+ '
src/__init__.py ADDED
File without changes
src/engine.py ADDED
@@ -0,0 +1,67 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from src.interfaces import Paper
2
+
3
+
4
+ class SearchAPI:
5
+ # fmt: off
6
+ SEARCH_PRIORITY = ["doi", "url", "year", "month", "venue", "authors", "title", "abstract"]
7
+ # fmt: on
8
+
9
+ def __init__(self) -> None:
10
+ self.papers: list[Paper] = []
11
+
12
+ def exhausted_search(self, query: dict[str, tuple[tuple[str]]]) -> list[Paper]:
13
+ """Exhausted search papers by matching query"""
14
+ papers = self.papers
15
+ for field in self.SEARCH_PRIORITY:
16
+ if field in query:
17
+ req = query[field]
18
+ paper_indices = []
19
+ for i, p in enumerate(papers):
20
+ for or_conditions in req:
21
+ matched = True
22
+ for and_cond_string in or_conditions:
23
+ if " " in and_cond_string:
24
+ if not and_cond_string.lower() in p[field].lower():
25
+ matched = False
26
+ break
27
+ else:
28
+ p_field = self.tokenize(p[field].lower())
29
+ if not and_cond_string.lower() in p_field:
30
+ matched = False
31
+ break
32
+ if matched:
33
+ paper_indices.append(i)
34
+ papers = [papers[i] for i in paper_indices]
35
+
36
+ if papers:
37
+ papers = sorted(papers, key=lambda p: (p.year, p.month), reverse=True)
38
+ return papers
39
+
40
+ def search(
41
+ self, query: dict[str, tuple[tuple[str]]], method: str = "exhausted"
42
+ ) -> list[Paper]:
43
+ """Search papers
44
+
45
+ Args:
46
+ query: A dict of queries on different field.
47
+ A query in a field is a tuple of strings, where strings are AND
48
+ and tuple means OR. Strings are case-insensitive.
49
+ e.g. {
50
+ "venue": (("EMNLP", ), ("ACL",)),
51
+ "title": (("parsing", "tree-crf"), ("event extraction",))
52
+ }
53
+ This query means we want to find papers in EMNLP or ACL,
54
+ AND the title either contains ("parsing" AND "tree-crf") OR "event extraction"
55
+ method: choice from:
56
+ - `exhausted`: brute force mathing
57
+
58
+ Returns:
59
+ a list of `Paper`
60
+ """
61
+ if method == "exhausted":
62
+ return self.exhausted_search(query)
63
+ else:
64
+ raise NotImplementedError
65
+
66
+ def tokenize(self, string: str) -> list[str]:
67
+ return string.lower().split()
src/interfaces/__init__.py ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from dataclasses import dataclass
2
+
3
+
4
+ @dataclass
5
+ class Paper:
6
+ title: str
7
+ authors: str # People Name1, People Name2: split by `, `
8
+ abstract: str
9
+ url: str
10
+ doi: str
11
+ venue: str
12
+ year: int
13
+ month: int
14
+
15
+ def as_dict(self):
16
+ return {
17
+ "title": self.title,
18
+ "author": self.authors,
19
+ "abstract": self.abstract,
20
+ "url": self.url,
21
+ "doi": self.doi,
22
+ "venue": self.venue,
23
+ }
24
+
25
+ def __getitem__(self, attr_key: str):
26
+ return getattr(self, attr_key)
src/interfaces/aclanthology.py ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import pathlib
2
+ import re
3
+
4
+ from src.engine import SearchAPI
5
+ from src.interfaces import Paper
6
+ from src.utils import load_json, parse_bib_month
7
+
8
+
9
+ class AclanthologyPaperList(SearchAPI):
10
+ def __init__(self, cache_filepath: pathlib.Path) -> None:
11
+ super().__init__()
12
+
13
+ data = load_json(cache_filepath)
14
+
15
+ self.papers = []
16
+ for d in data:
17
+ authors = ", ".join(
18
+ [self.extract_author_full(author) for author in d.get("authors", [])]
19
+ )
20
+ venue = d.get("venue", [])
21
+ if venue:
22
+ venue = venue[0]
23
+ year = int(d.get("year", "9999"))
24
+ month = parse_bib_month(d.get("month", "99"))
25
+ paper = Paper(
26
+ d.get("title", ""),
27
+ authors,
28
+ d.get("abstract", ""),
29
+ d.get("url", ""),
30
+ d.get("doi", ""),
31
+ venue,
32
+ year,
33
+ month,
34
+ )
35
+ if not paper.title:
36
+ continue
37
+ self.papers.append(paper)
38
+
39
+ def extract_author_full(self, name: str) -> str:
40
+ match = re.search(r".*?\((.*?)\)", name)
41
+ if match:
42
+ return match.group(1)
43
+ else:
44
+ return name
src/interfaces/arxiv.py ADDED
File without changes
src/interfaces/dblp.py ADDED
File without changes
src/utils.py ADDED
@@ -0,0 +1,151 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import functools
2
+ import gzip
3
+ import json
4
+ import pathlib
5
+ import re
6
+ import shutil
7
+
8
+ import requests
9
+ from tqdm.auto import tqdm
10
+
11
+ from src.interfaces import Paper
12
+
13
+
14
+ def download(url: str, filepath: str) -> pathlib.Path:
15
+ """Download file from url
16
+
17
+ Returns:
18
+ filepath of the saved file
19
+ """
20
+ r = requests.get(url, stream=True, allow_redirects=True)
21
+ if r.status_code != 200:
22
+ r.raise_for_status() # Will only raise for 4xx codes, so...
23
+ raise RuntimeError(f"Request to {url} returned status code {r.status_code}")
24
+ file_size = int(r.headers.get("Content-Length", 0))
25
+
26
+ path = pathlib.Path(filepath).expanduser().resolve()
27
+ path.parent.mkdir(parents=True, exist_ok=True)
28
+
29
+ desc = "(Unknown total file size)" if file_size == 0 else ""
30
+ r.raw.read = functools.partial(
31
+ r.raw.read, decode_content=True
32
+ ) # Decompress if needed
33
+ with tqdm.wrapattr(r.raw, "read", total=file_size, desc=desc) as r_raw:
34
+ with path.open("wb") as f:
35
+ shutil.copyfileobj(r_raw, f)
36
+
37
+ return path
38
+
39
+
40
+ def parse_bib(
41
+ input_filepath: pathlib.Path, output_filepath: pathlib.Path
42
+ ) -> list[dict]:
43
+ if input_filepath.suffix == ".gz":
44
+ open_func = gzip.open
45
+ else:
46
+ open_func = open
47
+
48
+ data = []
49
+ with open_func(input_filepath, "rt", encoding="utf8") as fin:
50
+ tot_bib_string = fin.read()
51
+ tot_bib_string = re.sub(
52
+ r" and\n\s+", " and ", tot_bib_string, flags=re.MULTILINE
53
+ )
54
+ tot_entries = tot_bib_string.count("@")
55
+ for bib in tqdm(
56
+ re.finditer(
57
+ r"@(\w+)\{(.+?),\n(.*?)\}$",
58
+ tot_bib_string,
59
+ flags=re.MULTILINE | re.DOTALL,
60
+ ),
61
+ desc="parse bib",
62
+ total=tot_entries,
63
+ ):
64
+ bib_type = bib.group(1)
65
+ bib_key = bib.group(2)
66
+ bib_content = {}
67
+ content_string = bib.group(3).strip()
68
+ for val in re.finditer(
69
+ r"\s*(.*?)\s*=\s*(.+?),$\n", content_string, flags=re.MULTILINE
70
+ ):
71
+ bib_content[val.group(1).strip()] = (
72
+ val.group(2).strip().removeprefix('"').removesuffix('"')
73
+ )
74
+ ins = {"type": bib_type, "key": bib_key, "content": bib_content}
75
+
76
+ if bib_type == "article":
77
+ ins["content"]["volume"] = ins["content"]["journal"]
78
+ elif bib_type == "inproceedings":
79
+ ins["content"]["volume"] = ins["content"]["booktitle"]
80
+
81
+ data.append(ins)
82
+
83
+ with open_func(output_filepath, "wt", encoding="utf8") as fout:
84
+ json.dump(data, fout, ensure_ascii=False)
85
+
86
+ return data
87
+
88
+
89
+ # fmt: off
90
+ MONTH_MAP = {
91
+ "january": 1, "february": 2, "march": 3, "april": 4, "may": 5, "june": 6, "july": 7, "august": 8, "september": 9, "october": 10, "november": 11, "december": 12,
92
+ "jan": 1, "feb": 2, "mar": 3, "apr": 4, "may": 5, "jun": 6, "jul": 7, "aug": 8, "sep": 9, "oct": 10, "nov": 11, "dec": 12,
93
+ }
94
+ # fmt: one
95
+
96
+
97
+ def parse_bib_month(month: str) -> int:
98
+ if month.isdigit():
99
+ return int(month)
100
+ elif month.lower() in MONTH_MAP:
101
+ return MONTH_MAP[month.lower()]
102
+ else:
103
+ return 99
104
+
105
+
106
+ def load_json(filepath: pathlib.Path) -> dict | list:
107
+ if isinstance(filepath, str):
108
+ filepath = pathlib.Path(filepath)
109
+
110
+ if filepath.suffix == ".gz":
111
+ open_func = gzip.open
112
+ else:
113
+ open_func = open
114
+
115
+ with open_func(filepath, "rt", encoding="utf8") as fin:
116
+ data = json.load(fin)
117
+ return data
118
+
119
+
120
+ def dump_json(data: list | dict, filepath: str | pathlib.Path):
121
+ with open(filepath, "wt", encoding="utf8") as fout:
122
+ json.dump(data, fout, ensure_ascii=False)
123
+
124
+
125
+ def dump_list_to_markdown_checklist(str_list: list[str], filepath: str | pathlib.Path):
126
+ md_string = ""
127
+ for string in str_list:
128
+ md_string += f"- [ ] {string}\n"
129
+
130
+ if isinstance(filepath, str):
131
+ filepath = pathlib.Path(filepath)
132
+ if not filepath.parent.exists():
133
+ filepath.parent.mkdir(parents=True)
134
+
135
+ with open(filepath, "wt", encoding="utf8") as fout:
136
+ fout.write(f"{md_string}")
137
+
138
+
139
+ def dump_paper_list_to_markdown_checklist(papers: list[Paper], filepath: str | pathlib.Path):
140
+ string_list = [
141
+ f"[{paper.venue.upper()}, {paper.year}] [{paper.title}]({paper.url})"
142
+ for paper in papers
143
+ ]
144
+ dump_list_to_markdown_checklist(string_list, filepath)
145
+
146
+
147
+ if __name__ == "__main__":
148
+ parse_bib(
149
+ pathlib.Path("cache/anthology+abstracts.bib.gz"),
150
+ pathlib.Path("cache/anthology+abstracts.json.gz"),
151
+ )
tests/__init__.py ADDED
File without changes
tests/test_utils.py ADDED
@@ -0,0 +1,216 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import re
2
+
3
+
4
+ def test_parse_bib():
5
+ string = """@proceedings{wsc-2023-sanskrit,
6
+ title = "Proceedings of the Computational Sanskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
7
+ editor = "Kulkarni, Amba and
8
+ Hellwig, Oliver",
9
+ month = jan,
10
+ year = "2023",
11
+ address = "Canberra, Australia (Online mode)",
12
+ publisher = "Association for Computational Linguistics",
13
+ url = "https://aclanthology.org/2023.wsc-csdh.0",
14
+ }
15
+ @inproceedings{krishna-etal-2023-neural,
16
+ title = "Neural Approaches for Data Driven Dependency Parsing in {S}anskrit",
17
+ author = "Krishna, Amrith and
18
+ Gupta, Ashim and
19
+ Garasangi, Deepak and
20
+ Sandhan, Jeevnesh and
21
+ Satuluri, Pavankumar and
22
+ Goyal, Pawan",
23
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
24
+ month = jan,
25
+ year = "2023",
26
+ address = "Canberra, Australia (Online mode)",
27
+ publisher = "Association for Computational Linguistics",
28
+ url = "https://aclanthology.org/2023.wsc-csdh.1",
29
+ pages = "1--20",
30
+ }
31
+ @inproceedings{sandhan-etal-2023-evaluating,
32
+ title = "Evaluating Neural Word Embeddings for {S}anskrit",
33
+ author = "Sandhan, Jivnesh and
34
+ Paranjay, Om Adideva and
35
+ Digumarthi, Komal and
36
+ Behra, Laxmidhar and
37
+ Goyal, Pawan",
38
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
39
+ month = jan,
40
+ year = "2023",
41
+ address = "Canberra, Australia (Online mode)",
42
+ publisher = "Association for Computational Linguistics",
43
+ url = "https://aclanthology.org/2023.wsc-csdh.2",
44
+ pages = "21--37",
45
+ }
46
+ @inproceedings{sriram-etal-2023-validation,
47
+ title = "Validation and Normalization of {DCS} corpus and Development of the {S}anskrit Heritage Engine{'}s Segmenter",
48
+ author = "Sriram, Krishnan and
49
+ Kulkarni, Amba and
50
+ Huet, G{\'e}rard",
51
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
52
+ month = jan,
53
+ year = "2023",
54
+ address = "Canberra, Australia (Online mode)",
55
+ publisher = "Association for Computational Linguistics",
56
+ url = "https://aclanthology.org/2023.wsc-csdh.3",
57
+ pages = "38--58",
58
+ }
59
+ @inproceedings{sarkar-etal-2023-pre,
60
+ title = "Pre-annotation Based Approach for Development of a {S}anskrit Named Entity Recognition Dataset",
61
+ author = "Sujoy, Sarkar and
62
+ Krishna, Amrith and
63
+ Goyal, Pawan",
64
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
65
+ month = jan,
66
+ year = "2023",
67
+ address = "Canberra, Australia (Online mode)",
68
+ publisher = "Association for Computational Linguistics",
69
+ url = "https://aclanthology.org/2023.wsc-csdh.4",
70
+ pages = "59--70",
71
+ }
72
+ @inproceedings{maity-etal-2023-disambiguation,
73
+ title = "Disambiguation of Instrumental, Dative and Ablative Case suffixes in {S}anskrit",
74
+ author = "Maity, Malay and
75
+ Panchal, Sanjeev and
76
+ Kulkarni, Amba",
77
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
78
+ month = jan,
79
+ year = "2023",
80
+ address = "Canberra, Australia (Online mode)",
81
+ publisher = "Association for Computational Linguistics",
82
+ url = "https://aclanthology.org/2023.wsc-csdh.5",
83
+ pages = "71--88",
84
+ }
85
+ @inproceedings{mahesh-bhattacharya-2023-creation,
86
+ title = "Creation of a Digital Rig {V}edic Index (Anukramani) for Computational Linguistic Tasks",
87
+ author = "Mahesh, A V S D S and
88
+ Bhattacharya, Arnab",
89
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
90
+ month = jan,
91
+ year = "2023",
92
+ address = "Canberra, Australia (Online mode)",
93
+ publisher = "Association for Computational Linguistics",
94
+ url = "https://aclanthology.org/2023.wsc-csdh.6",
95
+ pages = "89--96",
96
+ }
97
+ @inproceedings{neill-2023-skrutable,
98
+ title = "Skrutable: Another Step Toward Effective {S}anskrit Meter Identification",
99
+ author = "Neill, Tyler",
100
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
101
+ month = jan,
102
+ year = "2023",
103
+ address = "Canberra, Australia (Online mode)",
104
+ publisher = "Association for Computational Linguistics",
105
+ url = "https://aclanthology.org/2023.wsc-csdh.7",
106
+ pages = "97--112",
107
+ }
108
+ @inproceedings{terdalkar-bhattacharya-2023-chandojnanam,
109
+ title = "Chandojnanam: A {S}anskrit Meter Identification and Utilization System",
110
+ author = "Terdalkar, Hrishikesh and
111
+ Bhattacharya, Arnab",
112
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
113
+ month = jan,
114
+ year = "2023",
115
+ address = "Canberra, Australia (Online mode)",
116
+ publisher = "Association for Computational Linguistics",
117
+ url = "https://aclanthology.org/2023.wsc-csdh.8",
118
+ pages = "113--127",
119
+ }
120
+ @inproceedings{ajotikar-scharf-2023-development,
121
+ title = "Development of a {TEI} standard for digital {S}anskrit texts containing commentaries: A pilot study of Bhaṭṭti{'}s R{=a}vaṇavadha with Mallin{=a}tha{'}s commentary on the first canto",
122
+ author = "Ajotikar, Tanuja P and
123
+ Scharf, Peter M",
124
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
125
+ month = jan,
126
+ year = "2023",
127
+ address = "Canberra, Australia (Online mode)",
128
+ publisher = "Association for Computational Linguistics",
129
+ url = "https://aclanthology.org/2023.wsc-csdh.9",
130
+ pages = "128--145",
131
+ }
132
+ @inproceedings{scharf-chauhan-2023-ramopakhyana,
133
+ title = "R{=a}mop{=a}khy{=a}na: A Web-based reader and index",
134
+ author = "Scharf, Peter M and
135
+ Chauhan, Dhruv",
136
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
137
+ month = jan,
138
+ year = "2023",
139
+ address = "Canberra, Australia (Online mode)",
140
+ publisher = "Association for Computational Linguistics",
141
+ url = "https://aclanthology.org/2023.wsc-csdh.10",
142
+ pages = "146--154",
143
+ }
144
+ @inproceedings{terdalkar-etal-2023-semantic,
145
+ title = "Semantic Annotation and Querying Framework based on Semi-structured Ayurvedic Text",
146
+ author = "Terdalkar, Hrishikesh and
147
+ Bhattacharya, Arnab and
148
+ Dubey, Madhulika and
149
+ Ramamurthy, S and
150
+ Singh, Bhavna Naneria",
151
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
152
+ month = jan,
153
+ year = "2023",
154
+ address = "Canberra, Australia (Online mode)",
155
+ publisher = "Association for Computational Linguistics",
156
+ url = "https://aclanthology.org/2023.wsc-csdh.11",
157
+ pages = "155--173",
158
+ }
159
+ @inproceedings{susarla-etal-2023-shaastra,
160
+ title = "Shaastra Maps: Enabling Conceptual Exploration of {I}ndic Shaastra Texts",
161
+ author = "Susarla, Sai and
162
+ Jammalamadaka, Suryanarayana and
163
+ Nishankar, Vaishnavi and
164
+ Panuganti, Siva and
165
+ Ryali, Anupama and
166
+ Sushrutha, S",
167
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
168
+ month = jan,
169
+ year = "2023",
170
+ address = "Canberra, Australia (Online mode)",
171
+ publisher = "Association for Computational Linguistics",
172
+ url = "https://aclanthology.org/2023.wsc-csdh.12",
173
+ pages = "174--187",
174
+ }
175
+ @inproceedings{hellwig-etal-2023-vedic,
176
+ title = "The {V}edic corpus as a graph. An updated version of Bloomfields {V}edic Concordance",
177
+ author = "Hellwig, Oliver and
178
+ Sellmer, Sven and
179
+ Amano, Kyoko",
180
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
181
+ month = jan,
182
+ year = "2023",
183
+ address = "Canberra, Australia (Online mode)",
184
+ publisher = "Association for Computational Linguistics",
185
+ url = "https://aclanthology.org/2023.wsc-csdh.13",
186
+ pages = "188--200",
187
+ }
188
+ @inproceedings{harnsukworapanich-supphipat-2023-transmission,
189
+ title = "The transmission of the Buddha{'}s teachings in the digital age",
190
+ author = "Harnsukworapanich, Sumachaya and
191
+ Supphipat, Phatchareporn",
192
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
193
+ month = jan,
194
+ year = "2023",
195
+ address = "Canberra, Australia (Online mode)",
196
+ publisher = "Association for Computational Linguistics",
197
+ url = "https://aclanthology.org/2023.wsc-csdh.14",
198
+ pages = "201--212",
199
+ }
200
+ @inproceedings{zigmond-2023-distinguishing,
201
+ title = "Distinguishing Commentary from Canon: Experiments in P{=a}li Computational Linguistics",
202
+ author = "Zigmond, Dan",
203
+ booktitle = "Proceedings of the Computational {S}anskrit & Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
204
+ month = jan,
205
+ year = "2023",
206
+ address = "Canberra, Australia (Online mode)",
207
+ publisher = "Association for Computational Linguistics",
208
+ url = "https://aclanthology.org/2023.wsc-csdh.15",
209
+ pages = "213--222",
210
+ }""" # noqa: W605
211
+ new_string = re.sub(r"and$\n\s+", "and ", string, flags=re.MULTILINE)
212
+ print(new_string)
213
+
214
+
215
+ if __name__ == "__main__":
216
+ test_parse_bib()
tox.ini ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ [flake8]
2
+ ignore=
3
+ # line length
4
+ E501
5
+
6
+ exclude=
7
+ cache/