|
--- |
|
dataset_info: |
|
features: |
|
- name: uid |
|
dtype: int32 |
|
- name: NNQT_question |
|
dtype: string |
|
- name: paraphrased_question |
|
dtype: string |
|
- name: question |
|
dtype: string |
|
- name: simplified_query |
|
dtype: string |
|
- name: sparql_dbpedia18 |
|
dtype: string |
|
- name: sparql_wikidata |
|
dtype: string |
|
- name: answer |
|
list: string |
|
- name: solved_answer |
|
list: string |
|
- name: subgraph |
|
dtype: string |
|
- name: template |
|
dtype: string |
|
- name: template_id |
|
dtype: string |
|
- name: template_index |
|
dtype: int32 |
|
splits: |
|
- name: train |
|
num_bytes: 241621115 |
|
num_examples: 21101 |
|
- name: validation |
|
num_bytes: 11306539 |
|
num_examples: 3010 |
|
- name: test |
|
num_bytes: 21146458 |
|
num_examples: 6024 |
|
download_size: 79003648 |
|
dataset_size: 274074112 |
|
task_categories: |
|
- question-answering |
|
- text-generation |
|
tags: |
|
- qa |
|
- knowledge-graph |
|
- sparql |
|
language: |
|
- en |
|
--- |
|
|
|
|
|
# Dataset Card for LC-QuAD 2.0 - SPARQLtoText version |
|
|
|
## Table of Contents |
|
- [Dataset Card for LC-QuAD 2.0 - SPARQLtoText version](#dataset-card-for-lc-quad-20---sparqltotext-version) |
|
- [Table of Contents](#table-of-contents) |
|
- [Dataset Description](#dataset-description) |
|
- [Dataset Summary](#dataset-summary) |
|
- [New field `simplified_query`](#new-field-simplified_query) |
|
- [New split "valid"](#new-split-valid) |
|
- [Supported tasks](#supported-tasks) |
|
- [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 [LC-QuAD 2.0](https://huggingface.co./datasets/lc_quad) for the SPARQL-to-Text task |
|
|
|
#### New field `simplified_query` |
|
|
|
New field is named "simplified_query". It results from applying the following step on the field "query": |
|
|
|
* Replacing URIs with a simpler format with prefix "resource:", "property:" and "ontology:". |
|
|
|
* Spacing the delimiters `(`, `{`, `.`, `}`, `)`. |
|
|
|
* Adding diversity to some filters which test a number (`contains ( ?var, 'number' )` can become `contains ?var = number` |
|
|
|
* Randomizing the variables names |
|
|
|
* Shuffling the clauses |
|
|
|
#### New split "valid" |
|
|
|
A validation set was randonly extracted from the test set to represent 10% of the whole dataset. |
|
|
|
### Supported tasks |
|
|
|
- Knowledge-based question-answering |
|
- Text-to-SPARQL conversion |
|
- SPARQL-to-Text conversion |
|
|
|
### Languages |
|
|
|
- English |
|
|
|
## Dataset Structure |
|
|
|
The corpus follows the global architecture from the original version of CSQA (https://amritasaha1812.github.io/CSQA/). |
|
|
|
There is one directory of the train, dev, and test sets, respectively. |
|
|
|
Dialogues are stored in separate directories, 100 dialogues per directory. |
|
|
|
Finally, each dialogue is stored in a JSON file as a list of turns. |
|
|
|
### 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 | 21,000 | 3,000 | 6,000 | |
|
| NL question per query | 1 | |
|
| Characters per query | 108 (± 36) | |
|
| Tokens per question | 10.6 (± 3.9) | |
|
|
|
|
|
## 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 |
|
@inproceedings{dubey2017lc2, |
|
title={LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia}, |
|
author={Dubey, Mohnish and Banerjee, Debayan and Abdelkawi, Abdelrahman and Lehmann, Jens}, |
|
booktitle={Proceedings of the 18th International Semantic Web Conference (ISWC)}, |
|
year={2019}, |
|
organization={Springer} |
|
} |
|
``` |
|
|
