Orange/simplequestions-sparqltotext

Name: Orange/simplequestions-sparqltotext
Creator: Orange
Published: 2024-06-22T08:39:37+08:00

Hugging Face2024-01-11 更新2024-06-22 收录

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数据链接：

https://hf-mirror.com/datasets/Orange/simplequestions-sparqltotext 数据链接链接失效反馈

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资源简介：

--- dataset_info: features: - name: original_nl_question dtype: string - name: recased_nl_question dtype: string - name: sparql_query dtype: string - name: verbalized_sparql_query dtype: string - name: nl_subject dtype: string - name: nl_property dtype: string - name: nl_object dtype: string - name: nl_answer dtype: string - name: rdf_subject dtype: string - name: rdf_property dtype: string - name: rdf_object dtype: string - name: rdf_answer dtype: string - name: rdf_target dtype: string splits: - name: train num_bytes: 11403929 num_examples: 34374 - name: validation num_bytes: 1614051 num_examples: 4867 - name: test num_bytes: 3304281 num_examples: 9961 download_size: 7595264 dataset_size: 16322261 task_categories: - question-answering - text-generation tags: - qa - knowledge-graph - sparql language: - en --- # Dataset Card for SimpleQuestions-SPARQLtoText ## Table of Contents - [Dataset Card for SimpleQuestions-SPARQLtoText](#dataset-card-for-simplequestions-sparqltotext) - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [JSON fields](#json-fields) - [Format of the SPARQL queries](#format-of-the-sparql-queries) - [Answerable/unanswerable](#answerableunanswerable) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Types of questions](#types-of-questions) - [Data splits](#data-splits) - [Additional information](#additional-information) - [Related datasets](#related-datasets) - [Licencing information](#licencing-information) - [Citation information](#citation-information) - [This version of the corpus (with normalized SPARQL queries)](#this-version-of-the-corpus-with-normalized-sparql-queries) - [Original version](#original-version) ## Dataset Description - **Paper:** [SPARQL-to-Text Question Generation for Knowledge-Based Conversational Applications (AACL-IJCNLP 2022)](https://aclanthology.org/2022.aacl-main.11/) - **Point of Contact:** Gwénolé Lecorvé ### Dataset Summary Special version of [SimpleQuestions](https://github.com/askplatypus/wikidata-simplequestions) with SPARQL queries formatted for the SPARQL-to-Text task. #### JSON fields The original version of SimpleQuestions is a raw text file listing triples and the natural language question. A JSON version has been generated and augmented with the following fields: * `rdf_subject`, `rdf_property`, `rdf_object`: triple in the Wikidata format (IDs) * `nl_subject`, `nl_property`, `nl_object`: triple with labels retrieved from Wikidata. Some entities do not have labels, they are labelled as `UNDEFINED_LABEL` * `sparql_query`: SPARQL query with Wikidata IDs * `verbalized_sparql_query`: SPARQL query with labels * `original_nl_question`: original natural language question from SimpleQuestions. This is in **lower case**. * `recased_nl_question`: Version of `original_nl_question` where the named entities have been automatically recased based on the labels of the entities. #### Format of the SPARQL queries * Randomizing the variables names * Delimiters are spaced #### Answerable/unanswerable Some questions in SimpleQuestions cannot be answered. Hence, it originally comes with 2 versions for the train/valid/test sets: one with all entries, another with the answerable questions only. ### Languages - English ## Dataset Structure ### Types of questions Comparison of question types compared to related datasets: | | | [SimpleQuestions](https://huggingface.co/datasets/OrangeInnov/simplequestions-sparqltotext) | [ParaQA](https://huggingface.co/datasets/OrangeInnov/paraqa-sparqltotext) | [LC-QuAD 2.0](https://huggingface.co/datasets/OrangeInnov/lcquad_2.0-sparqltotext) | [CSQA](https://huggingface.co/datasets/OrangeInnov/csqa-sparqltotext) | [WebNLQ-QA](https://huggingface.co/datasets/OrangeInnov/webnlg-qa) | |--------------------------|-----------------|:---------------:|:------:|:-----------:|:----:|:---------:| | **Number of triplets in query** | 1 | ✓ | ✓ | ✓ | ✓ | ✓ | | | 2 | | ✓ | ✓ | ✓ | ✓ | | | More | | | ✓ | ✓ | ✓ | | **Logical connector between triplets** | Conjunction | ✓ | ✓ | ✓ | ✓ | ✓ | | | Disjunction | | | | ✓ | ✓ | | | Exclusion | | | | ✓ | ✓ | | **Topology of the query graph** | Direct | ✓ | ✓ | ✓ | ✓ | ✓ | | | Sibling | | ✓ | ✓ | ✓ | ✓ | | | Chain | | ✓ | ✓ | ✓ | ✓ | | | Mixed | | | ✓ | | ✓ | | | Other | | ✓ | ✓ | ✓ | ✓ | | **Variable typing in the query** | None | ✓ | ✓ | ✓ | ✓ | ✓ | | | Target variable | | ✓ | ✓ | ✓ | ✓ | | | Internal variable | | ✓ | ✓ | ✓ | ✓ | | **Comparisons clauses** | None | ✓ | ✓ | ✓ | ✓ | ✓ | | | String | | | ✓ | | ✓ | | | Number | | | ✓ | ✓ | ✓ | | | Date | | | ✓ | | ✓ | | **Superlative clauses** | No | ✓ | ✓ | ✓ | ✓ | ✓ | | | Yes | | | | ✓ | | | **Answer type** | Entity (open) | ✓ | ✓ | ✓ | ✓ | ✓ | | | Entity (closed) | | | | ✓ | ✓ | | | Number | | | ✓ | ✓ | ✓ | | | Boolean | | ✓ | ✓ | ✓ | ✓ | | **Answer cardinality** | 0 (unanswerable) | | | ✓ | | ✓ | | | 1 | ✓ | ✓ | ✓ | ✓ | ✓ | | | More | | ✓ | ✓ | ✓ | ✓ | | **Number of target variables** | 0 (⇒ ASK verb) | | ✓ | ✓ | ✓ | ✓ | | | 1 | ✓ | ✓ | ✓ | ✓ | ✓ | | | 2 | | | ✓ | | ✓ | | **Dialogue context** | Self-sufficient | ✓ | ✓ | ✓ | ✓ | ✓ | | | Coreference | | | | ✓ | ✓ | | | Ellipsis | | | | ✓ | ✓ | | **Meaning** | Meaningful | ✓ | ✓ | ✓ | ✓ | ✓ | | | Non-sense | | | | | ✓ | ### Data splits Text verbalization is only available for a subset of the test set, referred to as *challenge set*. Other sample only contain dialogues in the form of follow-up sparql queries. | | Train | Validation | Test | | --------------------- | ---------- | ---------- | ---------- | | Questions | 34,000 | 5,000 | 10,000 | | NL question per query | 1 | | Characters per query | 70 (± 10) | | Tokens per question | 7.4 (± 2.1) | ## Additional information ### Related datasets This corpus is part of a set of 5 datasets released for SPARQL-to-Text generation, namely: - Non conversational datasets - [SimpleQuestions](https://huggingface.co/datasets/OrangeInnov/simplequestions-sparqltotext) (from https://github.com/askplatypus/wikidata-simplequestions) - [ParaQA](https://huggingface.co/datasets/OrangeInnov/paraqa-sparqltotext) (from https://github.com/barshana-banerjee/ParaQA) - [LC-QuAD 2.0](https://huggingface.co/datasets/OrangeInnov/lcquad_2.0-sparqltotext) (from http://lc-quad.sda.tech/) - Conversational datasets - [CSQA](https://huggingface.co/datasets/OrangeInnov/csqa-sparqltotext) (from https://amritasaha1812.github.io/CSQA/) - [WebNLQ-QA](https://huggingface.co/datasets/OrangeInnov/webnlg-qa) (derived from https://gitlab.com/shimorina/webnlg-dataset/-/tree/master/release_v3.0) ### Licencing information * Content from original dataset: CC-BY 3.0 * New content: CC BY-SA 4.0 ### Citation information #### This version of the corpus (with normalized SPARQL queries) ```bibtex @inproceedings{lecorve2022sparql2text, title={SPARQL-to-Text Question Generation for Knowledge-Based Conversational Applications}, author={Lecorv\'e, Gw\'enol\'e and Veyret, Morgan and Brabant, Quentin and Rojas-Barahona, Lina M.}, journal={Proceedings of the Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (AACL-IJCNLP)}, year={2022} } ``` #### Original version ```bibtex @article{bordes2015large, title={Large-scale simple question answering with memory networks}, author={Bordes, Antoine and Usunier, Nicolas and Chopra, Sumit and Weston, Jason}, journal={arXiv preprint arXiv:1506.02075}, year={2015} } ```

The SimpleQuestions-SPARQLtoText dataset is a special version of SimpleQuestions designed for the SPARQL-to-Text task. It includes multiple fields such as original natural language questions, recased questions, SPARQL queries, and their verbalized versions, along with RDF format subjects, properties, objects, and answers. The dataset is divided into train, validation, and test sets, each containing different numbers of examples and bytes. Additionally, the dataset provides comparisons with related datasets, as well as licensing and citation information.

提供机构：

Orange

原始信息汇总