|
--- |
|
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} |
|
} |
|
|
|
``` |
|
|
