Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Japanese
Size:
10K - 100K
ArXiv:
License:
File size: 3,376 Bytes
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---
dataset_info:
- config_name: default
features:
- name: premise
dtype: large_string
- name: hypothesis
dtype: large_string
- name: template_num
dtype: int64
- name: time_format
dtype: large_string
- name: time_span
dtype: large_string
- name: category
dtype: large_string
- name: label
dtype:
class_label:
names:
'0': entailment
'1': neutral
'2': contradiction
splits:
- name: train
num_bytes: 2424590
num_examples: 9950
- name: test
num_bytes: 88516
num_examples: 348
download_size: 594545
dataset_size: 2513106
- config_name: template
features:
- name: id
dtype: int64
- name: premise
dtype: large_string
- name: hypothesis
dtype: large_string
- name: entailment
dtype: large_string
- name: contradiction
dtype: large_string
- name: ng time unit
dtype: large_string
- name: test time format
dtype: large_string
- name: category
dtype: large_string
splits:
- name: train
num_bytes: 26196
num_examples: 79
download_size: 9709
dataset_size: 26196
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- config_name: template
data_files:
- split: train
path: template/train-*
license: cc-by-sa-4.0
task_categories:
- text-classification
language:
- ja
tags:
- nli
- evaluation
- benchmark
pretty_name: >-
Jamp: Controlled Japanese Temporal Inference Dataset for Evaluating
Generalization Capacity of Language Models
---
# Jamp: Controlled Japanese Temporal Inference Dataset for Evaluating Generalization Capacity of Language Models
Jamp([tomo-vv/temporalNLI_dataset](https://github.com/tomo-vv/temporalNLI_dataset)) is the Japanese temporal inference benchmark.
This dataset consists of templates, test data, and training data.
Template subset containing template, time format, or time span in their names are split based on tense fragment, time format,
or time span, respectively.
## Dataset Details
### Dataset Description
- **Created by:** tomo-vv([email protected])
- **Language(s) (NLP):** Japanese
- **License:** CC BY-SA 4.0
### Dataset Sources
- **Repository:** [tomo-vv/temporalNLI_dataset](https://github.com/tomo-vv/temporalNLI_dataset)
- **Paper:** [Jamp: Controlled Japanese Temporal Inference Dataset for Evaluating Generalization Capacity of Language Models](https://aclanthology.org/2023.acl-srw.8) (Sugimoto et al., ACL 2023)
## Citation
**BibTeX:**
```
@inproceedings{sugimoto-etal-2023-jamp,
title = "Jamp: Controlled {J}apanese Temporal Inference Dataset for Evaluating Generalization Capacity of Language Models",
author = "Sugimoto, Tomoki and
Onoe, Yasumasa and
Yanaka, Hitomi",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-srw.8",
pages = "57--68",
}
```
**APA:**
Sugimoto, T., Onoe, Y., & Yanaka, H. (2023). Jamp: Controlled Japanese Temporal Inference Dataset for Evaluating Generalization Capacity of Language Models.
arXiv preprint arXiv:2306.10727. |