Datasets:
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---
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}
}
```
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