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--- |
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license: apache-2.0 |
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source: https://github.com/KGQA/KGQA-datasets |
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--- |
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# Dataset Card for Dataset Name |
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## Dataset Description |
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- **Homepage:** https://www.tau-nlp.sites.tau.ac.il/compwebq |
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- **Repository:** https://github.com/alontalmor/WebAsKB |
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- **Paper:** https://arxiv.org/abs/1803.06643 |
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- **Leaderboard:** https://www.tau-nlp.sites.tau.ac.il/compwebq-leaderboard |
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- **Point of Contact:** [email protected]. |
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### Dataset Summary |
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**A dataset for answering complex questions that require reasoning over multiple web snippets** |
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ComplexWebQuestions is a new dataset that contains a large set of complex questions in natural language, and can be used in multiple ways: |
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- By interacting with a search engine, which is the focus of our paper (Talmor and Berant, 2018); |
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- As a reading comprehension task: we release 12,725,989 web snippets that are relevant for the questions, and were collected during the development of our model; |
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- As a semantic parsing task: each question is paired with a SPARQL query that can be executed against Freebase to retrieve the answer. |
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### Supported Tasks and Leaderboards |
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[More Information Needed] |
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### Languages |
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- English |
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## Dataset Structure |
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QUESTION FILES |
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The dataset contains 34,689 examples divided into 27,734 train, 3,480 dev, 3,475 test. |
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each containing: |
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``` |
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"ID”: The unique ID of the example; |
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"webqsp_ID": The original WebQuestionsSP ID from which the question was constructed; |
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"webqsp_question": The WebQuestionsSP Question from which the question was constructed; |
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"machine_question": The artificial complex question, before paraphrasing; |
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"question": The natural language complex question; |
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"sparql": Freebase SPARQL query for the question. Note that the SPARQL was constructed for the machine question, the actual question after paraphrasing |
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may differ from the SPARQL. |
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"compositionality_type": An estimation of the type of compositionally. {composition, conjunction, comparative, superlative}. The estimation has not been manually verified, |
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the question after paraphrasing may differ from this estimation. |
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"answers": a list of answers each containing answer: the actual answer; answer_id: the Freebase answer id; aliases: freebase extracted aliases for the answer. |
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"created": creation time |
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``` |
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NOTE: test set does not contain “answer” field. For test evaluation please send email to |
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[email protected]. |
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WEB SNIPPET FILES |
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The snippets files consist of 12,725,989 snippets each containing |
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PLEASE DON”T USE CHROME WHEN DOWNLOADING THESE FROM DROPBOX (THE UNZIP COULD FAIL) |
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"question_ID”: the ID of related question, containing at least 3 instances of the same ID (full question, split1, split2); |
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"question": The natural language complex question; |
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"web_query": Query sent to the search engine. |
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“split_source”: 'noisy supervision split' or ‘ptrnet split’, please train on examples containing “ptrnet split” when comparing to Split+Decomp from https://arxiv.org/abs/1807.09623 |
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“split_type”: 'full_question' or ‘split_part1' or ‘split_part2’ please use ‘composition_answer’ in question of type composition and split_type: “split_part1” when training a reading comprehension model on splits as in Split+Decomp from https://arxiv.org/abs/1807.09623 (in the rest of the cases use the original answer). |
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"web_snippets": ~100 web snippets per query. Each snippet includes Title,Snippet. They are ordered according to Google results. |
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With a total of |
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10,035,571 training set snippets |
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1,350,950 dev set snippets |
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1,339,468 test set snippets |
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### Source Data |
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The original files can be found at this [dropbox link](https://www.dropbox.com/sh/7pkwkrfnwqhsnpo/AACuu4v3YNkhirzBOeeaHYala) |
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### Licensing Information |
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Not specified |
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### Citation Information |
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``` |
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@inproceedings{talmor2018web, |
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title={The Web as a Knowledge-Base for Answering Complex Questions}, |
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author={Talmor, Alon and Berant, Jonathan}, |
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booktitle={Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)}, |
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pages={641--651}, |
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year={2018} |
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} |
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``` |
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### Contributions |
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Thanks for [happen2me](https://github.com/happen2me) for contributing this dataset. |
