--- 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} } ```