update

README.md

@@ -0,0 +1,121 @@
+---
+license: cc-by-4-0
+pretty_name: SubjQA for question generation
+languages: en
+multilinguality: monolingual
+size_categories: 10K<n<100K
+source_datasets: subjqa
+task_categories: question-generation
+task_ids: question-generation
+---
+
+# Dataset Card for "qg_sqyadshifts"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
+- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
+
+### Dataset Summary
+Modified version of [SQuADShifts](https://modestyachts.github.io/squadshifts-website/index.html) for question generation (QG) task.
+
+### Supported Tasks and Leaderboards
+* `question-generation`: The dataset can be used to train a model for question generation.
+  Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L score.
+
+### Languages
+English (en)
+
+## Dataset Structure
+### Data Instances
+#### plain_text
+An example of 'train' looks as follows.
+```
+{
+  "question": "How is book?",
+  "paragraph": "I am giving "Gone Girl" 3 stars, but only begrudgingly. In my mind, any book that takes me 3 months and 20 different tries to read is not worth 3 stars, especially a book written by an author I already respect. And I am not kidding, for me the first half of "Gone Girl" was a PURE TORTURE to read.Amy Dunn disappears on the day of her 5th wedding anniversary. All gradually uncovered evidence suggests that her husband, Nick, is somehow involved. Did he kill her? Was she kidnapped? What happened to Amy? One thing is clear, Nick and Amy's marriage wasn't as perfect as everybody thought.The first part of the novel is all about the investigation into Amy's disappearance, slow unraveling of Nick's dirty secrets, reminiscing about the troubled history of Nick and Amy's marriage as told in Amy's hidden diary. I strained and strained my brain trying to understand why this chunk of Gone Girl had no appeal to me whatsoever. The only answer I have is this: I am really not into reading about rich white people's problems. You want to whine to me about your dwindling trust fund? Losing your cushy New York job? Moving south and "only" renting a mansion there? Being unhappy because you have too much free time on your hands and you are used to only work as a hobby? You want to make fun of your lowly, un-posh neighbors and their casseroles? Well, I am not interested. I'd rather read about someone not necessarily likable, but at least worthy of my empathy, not waste my time on self-centered, spoiled, pathetic people who don't know what real problems are. Granted, characters in Flynn's previous novels ("Sharp Objects" and "Dark Places") are pretty pathetic and and at times revolting too, but I always felt some strange empathy towards them, not annoyance and boredom, like I felt reading about Amy and Nick's marriage voes.But then second part, with its wicked twist, changed everything. The story became much more exciting, dangerous and deranged. The main characters revealed sides to them that were quite shocking and VERY entertaining. I thought the Gillian Flynn I knew before finally unleashed her talent for writing utterly unlikable and crafty women. THEN I got invested in the story, THEN I cared.Was it too little too late though? I think it was. Something needed to be done to make "Gone Girl" a better read. Make it shorter? Cut out first part completely? I don't know. But because of my uneven experience with this novel I won't be able to recommend "Gone Girl" as readily as I did Flynn's earlier novels, even though I think this horror marriage story (it's not a true mystery, IMO) has some brilliantly written psycho goodness in it and an absolutely messed up ending that many loathed but I LOVED. I wish it didn't take so much time and patience to get to all of that...",
+  "answer": "any book that takes me 3 months and 20 different tries to read is not worth 3 stars",
+  "sentence": "In my mind, any book that takes me 3 months and 20 different tries to read is not worth 3 stars , especially a book written by an author I already respect.",
+  "paragraph_sentence": "I am giving "Gone Girl" 3 stars, but only begrudgingly. <hl> In my mind, any book that takes me 3 months and 20 different tries to read is not worth 3 stars , especially a book written by an author I already respect. <hl> And I am not kidding, for me the first half of "Gone Girl" was a PURE TORTURE to read. Amy Dunn disappears on the day of her 5th wedding anniversary. All gradually uncovered evidence suggests that her husband, Nick, is somehow involved. Did he kill her? Was she kidnapped? What happened to Amy? One thing is clear, Nick and Amy's marriage wasn't as perfect as everybody thought. The first part of the novel is all about the investigation into Amy's disappearance, slow unraveling of Nick's dirty secrets, reminiscing about the troubled history of Nick and Amy's marriage as told in Amy's hidden diary. I strained and strained my brain trying to understand why this chunk of Gone Girl had no appeal to me whatsoever. The only answer I have is this: I am really not into reading about rich white people's problems. You want to whine to me about your dwindling trust fund? Losing your cushy New York job? Moving south and "only" renting a mansion there? Being unhappy because you have too much free time on your hands and you are used to only work as a hobby? You want to make fun of your lowly, un-posh neighbors and their casseroles? Well, I am not interested. I'd rather read about someone not necessarily likable, but at least worthy of my empathy, not waste my time on self-centered, spoiled, pathetic people who don't know what real problems are. Granted, characters in Flynn's previous novels ("Sharp Objects" and "Dark Places") are pretty pathetic and and at times revolting too, but I always felt some strange empathy towards them, not annoyance and boredom, like I felt reading about Amy and Nick's marriage voes. But then second part, with its wicked twist, changed everything. The story became much more exciting, dangerous and deranged. The main characters revealed sides to them that were quite shocking and VERY entertaining. I thought the Gillian Flynn I knew before finally unleashed her talent for writing utterly unlikable and crafty women. THEN I got invested in the story, THEN I cared. Was it too little too late though? I think it was. Something needed to be done to make "Gone Girl" a better read. Make it shorter? Cut out first part completely? I don't know. But because of my uneven experience with this novel I won't be able to recommend "Gone Girl" as readily as I did Flynn's earlier novels, even though I think this horror marriage story (it's not a true mystery, IMO) has some brilliantly written psycho goodness in it and an absolutely messed up ending that many loathed but I LOVED. I wish it didn't take so much time and patience to get to all of that...",
+  "paragraph_answer": "I am giving "Gone Girl" 3 stars, but only begrudgingly. In my mind, <hl> any book that takes me 3 months and 20 different tries to read is not worth 3 stars <hl>, especially a book written by an author I already respect. And I am not kidding, for me the first half of "Gone Girl" was a PURE TORTURE to read.Amy Dunn disappears on the day of her 5th wedding anniversary. All gradually uncovered evidence suggests that her husband, Nick, is somehow involved. Did he kill her? Was she kidnapped? What happened to Amy? One thing is clear, Nick and Amy's marriage wasn't as perfect as everybody thought.The first part of the novel is all about the investigation into Amy's disappearance, slow unraveling of Nick's dirty secrets, reminiscing about the troubled history of Nick and Amy's marriage as told in Amy's hidden diary. I strained and strained my brain trying to understand why this chunk of Gone Girl had no appeal to me whatsoever. The only answer I have is this: I am really not into reading about rich white people's problems. You want to whine to me about your dwindling trust fund? Losing your cushy New York job? Moving south and "only" renting a mansion there? Being unhappy because you have too much free time on your hands and you are used to only work as a hobby? You want to make fun of your lowly, un-posh neighbors and their casseroles? Well, I am not interested. I'd rather read about someone not necessarily likable, but at least worthy of my empathy, not waste my time on self-centered, spoiled, pathetic people who don't know what real problems are. Granted, characters in Flynn's previous novels ("Sharp Objects" and "Dark Places") are pretty pathetic and and at times revolting too, but I always felt some strange empathy towards them, not annoyance and boredom, like I felt reading about Amy and Nick's marriage voes.But then second part, with its wicked twist, changed everything. The story became much more exciting, dangerous and deranged. The main characters revealed sides to them that were quite shocking and VERY entertaining. I thought the Gillian Flynn I knew before finally unleashed her talent for writing utterly unlikable and crafty women. THEN I got invested in the story, THEN I cared.Was it too little too late though? I think it was. Something needed to be done to make "Gone Girl" a better read. Make it shorter? Cut out first part completely? I don't know. But because of my uneven experience with this novel I won't be able to recommend "Gone Girl" as readily as I did Flynn's earlier novels, even though I think this horror marriage story (it's not a true mystery, IMO) has some brilliantly written psycho goodness in it and an absolutely messed up ending that many loathed but I LOVED. I wish it didn't take so much time and patience to get to all of that...",
+  "sentence_answer": "In my mind, <hl> any book that takes me 3 months and 20 different tries to read is not worth 3 stars <hl> , especially a book written by an author I already respect.",
+}
+```
+### Data Fields
+The data fields are the same among all splits.
+#### plain_text
+- `question`: a `string` feature. 
+- `paragraph`: a `string` feature.
+- `answer`: a `string` feature.
+- `sentence`: a `string` feature.
+- `paragraph_answer`: a `string` feature, which is same as the paragraph but the answer is highlighted by a special token `<hl>`.
+- `paragraph_sentence`: a `string` feature, which is same as the paragraph but a sentence containing the answer is highlighted by a special token `<hl>`.
+- `sentence_answer`: a `string` feature, which is same as the sentence but the answer is highlighted by a special token `<hl>`.
+
+Each of `paragraph_answer`, `paragraph_sentence`, and `sentence_answer` feature is assumed to be used to train a question generation model,
+but with different information. The `paragraph_answer` and `sentence_answer` features are for answer-aware question generation and 
+`paragraph_sentence` feature is for sentence-aware question generation.
+
+### Data Splits
+
+|   name      |test |
+|-------------|----:|
+|default (all)|4437 |
+| books       |636  |
+| movies      |723  |
+| grocery     |686  |
+| restaurants |822  |
+
+
+## Dataset Creation
+### Curation Rationale
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+### Source Data
+#### Initial Data Collection and Normalization
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+#### Who are the source language producers?
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+### Annotations
+#### Annotation process
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+#### Who are the annotators?
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+### Personal and Sensitive Information
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Considerations for Using the Data
+### Social Impact of Dataset
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+### Discussion of Biases
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+### Other Known Limitations
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Additional Information
+### Dataset Curators
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+### Licensing Information
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+### Citation Information
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

generate_reference_files.py

@@ -0,0 +1,13 @@
+import os
+from datasets import load_dataset
+
+os.makedirs('./reference_files', exist_ok=True)
+
+
+for split in ['test']:
+    for domain in ["default", 'new_wiki', 'nyt', 'reddit', 'amazon']:
+        dataset = load_dataset('asahi417/qg_squadshifts', domain, split=split)
+        for data in ['question', 'answer', 'sentence', 'paragraph']:
+            with open('./reference_files/{}-{}.{}txt'.format(data, split, "" if domain == 'default' else f"{domain}."), 'w') as f:
+                f.write('\n'.join(dataset[data]))
+

process.py

@@ -1,9 +1,9 @@
 """ Script to process raw SQuADshift file for Question Generation format
 cd data/processed
-gsplit -b 6M -d --additional-suffix=.jsonl new_wiki.test.jsonl new_wiki.test
-gsplit -b 6M -d --additional-suffix=.jsonl nyt.test.jsonl nyt.test
-gsplit -b 6M -d --additional-suffix=.jsonl reddit.test.jsonl reddit.test
-gsplit -b 6M -d --additional-suffix=.jsonl amazon.test.jsonl amazon.test
+gsplit -l 1500 -d --additional-suffix=.jsonl new_wiki.test.jsonl new_wiki.test
+gsplit -l 1500 -d --additional-suffix=.jsonl nyt.test.jsonl nyt.test
+gsplit -l 1500 -d --additional-suffix=.jsonl reddit.test.jsonl reddit.test
+gsplit -l 1500 -d --additional-suffix=.jsonl amazon.test.jsonl amazon.test
 
 rm -rf new_wiki.test.jsonl
 rm -rf nyt.test.jsonl
@@ -92,11 +92,12 @@ if __name__ == '__main__':
             tmp_dataset = dataset[_split]
             with open(f'{output}/{data_type}.{_split}.jsonl', 'w') as f:
                 for single_data in tqdm(tmp_dataset):
+                    question_str = single_data['question']  #.replace("\n", ".").replace('"', "'")
+                    paragraph_str = single_data['context']  #.replace("\n", ".").replace('"', "'")
                     answer_str = single_data['answers']['text']
-                    question_str = single_data['question']
-                    paragraph_str = single_data['context']
                     if type(answer_str) == list:
                         answer_str = answer_str[0]
+                    # answer_str = answer_str.replace("\n", ".").replace('"', "'")
                     assert type(answer_str) is str, answer_str
                     assert type(question_str) is str, question_str
                     assert type(paragraph_str) is str, paragraph_str

qg_squadshift.py → qg_squadshifts.py

@@ -1,11 +1,20 @@
+""" python -c "from datasets import load_dataset;load_dataset('.')" """
 import json
+from itertools import chain
 import datasets
 
 logger = datasets.logging.get_logger(__name__)
 _DESCRIPTION = """[SQuAD Shifts](https://modestyachts.github.io/squadshifts-website/index.html) dataset for question generation (QG) task."""
 _URL = 'https://huggingface.co/datasets/asahi417/qg_squadshift/raw/main/data/processed'
-_DOMAINS = ['new_wiki', 'nyt', 'reddit', 'amazon']
-_FILESIZE = [4, 5, 5, 5]
+_FILES = {
+    datasets.Split.TEST:
+        {
+            'new_wiki': [f'{_URL}/new_wiki.test{i:02d}.jsonl' for i in range(4)],
+            'nyt': [f'{_URL}/nyt.test{i:02d}.jsonl' for i in range(4)],
+            'reddit': [f'{_URL}/reddit.test{i:02d}.jsonl' for i in range(4)],
+            'amazon': [f'{_URL}/amazon.test{i:02d}.jsonl' for i in range(4)]
+        }
+}
 
 
 class QGSQuADShiftsConfig(datasets.BuilderConfig):
@@ -22,7 +31,7 @@ class QGSQuADShiftsConfig(datasets.BuilderConfig):
 class QGSQuADShifts(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIGS = [QGSQuADShiftsConfig(name="default", description="All domain.")]
-    BUILDER_CONFIGS += [QGSQuADShiftsConfig(name=i, description=i) for i in _DOMAINS]
+    BUILDER_CONFIGS += [QGSQuADShiftsConfig(name=i, description=i) for i in sorted(_FILES.keys())]
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -35,11 +44,7 @@ class QGSQuADShifts(datasets.GeneratorBasedBuilder):
                     "paragraph": datasets.Value("string"),
                     "sentence_answer": datasets.Value("string"),
                     "paragraph_answer": datasets.Value("string"),
-                    "paragraph_sentence": datasets.Value("string"),
-                    "paragraph_id": datasets.Value("string"),
-                    "question_subj_level": datasets.Value("int32"),
-                    "answer_subj_level": datasets.Value("int32"),
-                    "domain": datasets.Value("string"),
+                    "paragraph_sentence": datasets.Value("string")
                 }
             ),
             supervised_keys=None,
@@ -48,22 +53,10 @@ class QGSQuADShifts(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         if self.config.name == 'default':
-            downloaded_file = dl_manager.download_and_extract({
-                'train': [f"{_URL}/{i}.train.jsonl" for i in _DOMAINS],
-                'dev': [f"{_URL}/{i}.dev.jsonl" for i in _DOMAINS],
-                'test': [f"{_URL}/{i}.test.jsonl" for i in _DOMAINS]
-            })
+            downloaded_file = dl_manager.download_and_extract({k: list(chain(*list(v.values()))) for k, v in _FILES.items()})
         else:
-            downloaded_file = dl_manager.download_and_extract({
-                'train': [f"{_URL}/{self.config.name}.train.jsonl"],
-                'dev': [f"{_URL}/{self.config.name}.dev.jsonl"],
-                'test': [f"{_URL}/{self.config.name}.test.jsonl"]
-            })
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_file["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": downloaded_file["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepaths": downloaded_file["test"]})
-        ]
+            downloaded_file = dl_manager.download_and_extract({k: v[self.config.name] for k, v in _FILES.items()})
+        return [datasets.SplitGenerator(name=k, gen_kwargs={"filepaths": downloaded_file[k]}) for k in _FILES.keys()]
 
     def _generate_examples(self, filepaths):
         _key = 0