Datasets:
Tasks:
Question Answering
Sub-tasks:
extractive-qa
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
conversational-qa
License:
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - crowdsourced | |
| - expert-generated | |
| language: | |
| - en | |
| license: | |
| - unknown | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - extended|sharc | |
| task_categories: | |
| - question-answering | |
| task_ids: | |
| - extractive-qa | |
| paperswithcode_id: null | |
| pretty_name: SharcModified | |
| tags: | |
| - conversational-qa | |
| dataset_info: | |
| - config_name: mod | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: utterance_id | |
| dtype: string | |
| - name: source_url | |
| dtype: string | |
| - name: snippet | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: scenario | |
| dtype: string | |
| - name: history | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: evidence | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 15138034 | |
| num_examples: 21890 | |
| - name: validation | |
| num_bytes: 1474239 | |
| num_examples: 2270 | |
| download_size: 21197271 | |
| dataset_size: 16612273 | |
| - config_name: mod_dev_multi | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: utterance_id | |
| dtype: string | |
| - name: source_url | |
| dtype: string | |
| - name: snippet | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: scenario | |
| dtype: string | |
| - name: history | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: evidence | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| - name: all_answers | |
| sequence: string | |
| splits: | |
| - name: validation | |
| num_bytes: 1553940 | |
| num_examples: 2270 | |
| download_size: 2006124 | |
| dataset_size: 1553940 | |
| - config_name: history | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: utterance_id | |
| dtype: string | |
| - name: source_url | |
| dtype: string | |
| - name: snippet | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: scenario | |
| dtype: string | |
| - name: history | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: evidence | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 15083103 | |
| num_examples: 21890 | |
| - name: validation | |
| num_bytes: 1468604 | |
| num_examples: 2270 | |
| download_size: 21136658 | |
| dataset_size: 16551707 | |
| - config_name: history_dev_multi | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: utterance_id | |
| dtype: string | |
| - name: source_url | |
| dtype: string | |
| - name: snippet | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: scenario | |
| dtype: string | |
| - name: history | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: evidence | |
| list: | |
| - name: follow_up_question | |
| dtype: string | |
| - name: follow_up_answer | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| - name: all_answers | |
| sequence: string | |
| splits: | |
| - name: validation | |
| num_bytes: 1548305 | |
| num_examples: 2270 | |
| download_size: 2000489 | |
| dataset_size: 1548305 | |
| # Dataset Card for SharcModified | |
| ## 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) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [More info needed] | |
| - **Repository:** [github](https://github.com/nikhilweee/neural-conv-qa) | |
| - **Paper:** [Neural Conversational QA: Learning to Reason v.s. Exploiting Patterns](https://arxiv.org/abs/1909.03759) | |
| - **Leaderboard:** [More info needed] | |
| - **Point of Contact:** [More info needed] | |
| ### Dataset Summary | |
| ShARC, a conversational QA task, requires a system to answer user questions based on rules expressed in natural language text. | |
| However, it is found that in the ShARC dataset there are multiple spurious patterns that could be exploited by neural models. | |
| SharcModified is a new dataset which reduces the patterns identified in the original dataset. | |
| To reduce the sensitivity of neural models, for each occurence of an instance conforming to any of the patterns, | |
| we automatically construct alternatives where we choose to either replace the current instance with an alternative | |
| instance which does not exhibit the pattern; or retain the original instance. | |
| The modified ShARC has two versions sharc-mod and history-shuffled. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| The dataset is in english (en). | |
| ## Dataset Structure | |
| ### Data Instances | |
| Example of one instance: | |
| ``` | |
| { | |
| "annotation": { | |
| "answer": [ | |
| { | |
| "paragraph_reference": { | |
| "end": 64, | |
| "start": 35, | |
| "string": "syndactyly affecting the feet" | |
| }, | |
| "sentence_reference": { | |
| "bridge": false, | |
| "end": 64, | |
| "start": 35, | |
| "string": "syndactyly affecting the feet" | |
| } | |
| } | |
| ], | |
| "explanation_type": "single_sentence", | |
| "referential_equalities": [ | |
| { | |
| "question_reference": { | |
| "end": 40, | |
| "start": 29, | |
| "string": "webbed toes" | |
| }, | |
| "sentence_reference": { | |
| "bridge": false, | |
| "end": 11, | |
| "start": 0, | |
| "string": "Webbed toes" | |
| } | |
| } | |
| ], | |
| "selected_sentence": { | |
| "end": 67, | |
| "start": 0, | |
| "string": "Webbed toes is the common name for syndactyly affecting the feet . " | |
| } | |
| }, | |
| "example_id": 9174646170831578919, | |
| "original_nq_answers": [ | |
| { | |
| "end": 45, | |
| "start": 35, | |
| "string": "syndactyly" | |
| } | |
| ], | |
| "paragraph_text": "Webbed toes is the common name for syndactyly affecting the feet . It is characterised by the fusion of two or more digits of the feet . This is normal in many birds , such as ducks ; amphibians , such as frogs ; and mammals , such as kangaroos . In humans it is considered unusual , occurring in approximately one in 2,000 to 2,500 live births .", | |
| "question": "what is the medical term for webbed toes", | |
| "sentence_starts": [ | |
| 0, | |
| 67, | |
| 137, | |
| 247 | |
| ], | |
| "title_text": "Webbed toes", | |
| "url": "https: //en.wikipedia.org//w/index.php?title=Webbed_toes&oldid=801229780" | |
| } | |
| ``` | |
| ### Data Fields | |
| - `example_id`: a unique integer identifier that matches up with NQ | |
| - `title_text`: the title of the wikipedia page containing the paragraph | |
| - `url`: the url of the wikipedia page containing the paragraph | |
| - `question`: a natural language question string from NQ | |
| - `paragraph_text`: a paragraph string from a wikipedia page containing the answer to question | |
| - `sentence_starts`: a list of integer character offsets indicating the start of sentences in the paragraph | |
| - `original_nq_answers`: the original short answer spans from NQ | |
| - `annotation`: the QED annotation, a dictionary with the following items and further elaborated upon below: | |
| - `referential_equalities`: a list of dictionaries, one for each referential equality link annotated | |
| - `answer`: a list of dictionaries, one for each short answer span | |
| - `selected_sentence`: a dictionary representing the annotated sentence in the passage | |
| - `explanation_type`: one of "single_sentence", "multi_sentence", or "none" | |
| ### Data Splits | |
| The dataset is split into training and validation splits. | |
| | | train | validation | | |
| |--------------|------:|-----------:| | |
| | N. Instances | 7638 | 1355 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| [More Information Needed] | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| [More Information Needed] | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed] | |
| ### Licensing Information | |
| Unknown. | |
| ### Citation Information | |
| ``` | |
| @misc{lamm2020qed, | |
| title={QED: A Framework and Dataset for Explanations in Question Answering}, | |
| author={Matthew Lamm and Jennimaria Palomaki and Chris Alberti and Daniel Andor and Eunsol Choi and Livio Baldini Soares and Michael Collins}, | |
| year={2020}, | |
| eprint={2009.06354}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset. |