| | --- |
| | license: cc-by-sa-4.0 |
| | dataset_info: |
| | features: |
| | - name: category |
| | dtype: string |
| | - name: size |
| | dtype: int32 |
| | - name: id |
| | dtype: string |
| | - name: eid |
| | dtype: string |
| | - name: original_triple_sets |
| | list: |
| | - name: subject |
| | dtype: string |
| | - name: property |
| | dtype: string |
| | - name: object |
| | dtype: string |
| | - name: modified_triple_sets |
| | list: |
| | - name: subject |
| | dtype: string |
| | - name: property |
| | dtype: string |
| | - name: object |
| | dtype: string |
| | - name: shape |
| | dtype: string |
| | - name: shape_type |
| | dtype: string |
| | - name: lex |
| | sequence: |
| | - name: comment |
| | dtype: string |
| | - name: lid |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: lang |
| | dtype: string |
| | - name: test_category |
| | dtype: string |
| | - name: dbpedia_links |
| | sequence: string |
| | - name: links |
| | sequence: string |
| | - name: graph |
| | list: |
| | list: string |
| | - name: main_entity |
| | dtype: string |
| | - name: mappings |
| | list: |
| | - name: modified |
| | dtype: string |
| | - name: readable |
| | dtype: string |
| | - name: graph |
| | dtype: string |
| | - name: dialogue |
| | list: |
| | - name: question |
| | list: |
| | - name: source |
| | dtype: string |
| | - name: text |
| | dtype: string |
| | - name: graph_query |
| | dtype: string |
| | - name: readable_query |
| | dtype: string |
| | - name: graph_answer |
| | list: string |
| | - name: readable_answer |
| | list: string |
| | - name: type |
| | list: string |
| | splits: |
| | - name: train |
| | num_bytes: 33200723 |
| | num_examples: 10016 |
| | - name: validation |
| | num_bytes: 4196972 |
| | num_examples: 1264 |
| | - name: test |
| | num_bytes: 4990595 |
| | num_examples: 1417 |
| | - name: challenge |
| | num_bytes: 420551 |
| | num_examples: 100 |
| | download_size: 9637685 |
| | dataset_size: 42808841 |
| | task_categories: |
| | - conversational |
| | - question-answering |
| | - text-generation |
| | tags: |
| | - qa |
| | - knowledge-graph |
| | - sparql |
| | language: |
| | - en |
| | --- |
| | |
| | # Dataset Card for WEBNLG-QA |
| |
|
| | ## 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 |
| |
|
| | WEBNLG-QA is a conversational question answering dataset grounded on WEBNLG. It consists in a set of question-answering dialogues (follow-up question-answer pairs) based on short paragraphs of text. Each paragraph is associated a knowledge graph (from WEBNLG). The questions are associated with SPARQL queries. |
| |
|
| | ### Supported tasks |
| |
|
| | * Knowledge-based question-answering |
| | * SPARQL-to-Text conversion |
| |
|
| |
|
| | #### Knowledge based question-answering |
| |
|
| | Below is an example of dialogue: |
| | - Q1: What is used as an instrument is Sludge Metal or in Post-metal? |
| | - A1: Singing, Synthesizer |
| | - Q2: And what about Sludge Metal in particular? |
| | - A2: Singing |
| | - Q3: Does the Year of No Light album Nord belong to this genre? |
| | - A3: Yes. |
| |
|
| | #### SPARQL-to-Text Question Generation |
| |
|
| | SPARQL-to-Text question generation refers to the task of converting a SPARQL query into a natural language question, eg: |
| |
|
| | ```SQL |
| | SELECT (COUNT(?country) as ?answer) |
| | WHERE { ?country property:member_of resource:Europe . |
| | ?country property:population ?n . |
| | FILTER ( ?n > 10000000 ) |
| | } |
| | ``` |
| |
|
| | could be converted into: |
| |
|
| | ```txt |
| | How many European countries have more than 10 million inhabitants? |
| | ``` |
| |
|
| | ## 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 | Challenge | |
| | | --------------------- | ---------- | ---------- | ---------- | ------------ | |
| | | Questions | 27727 | 3485 | 4179 | 332 | |
| | | Dialogues | 1001 | 1264 | 1417 | 100 | |
| | | NL question per query | 0 | 0 | 0 | 2 | |
| | | Characters per query | 129 (± 43) | 131 (± 45) | 122 (± 45) | 113 (± 38) | |
| | | Tokens per question | - | - | - | 8.4 (± 4.5) | |
| |
|
| |
|
| | ## 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-SA 4.0 |
| | * New content: CC BY-SA 4.0 |
| | |
| | |
| | ### Citation information |
| | |
| | #### This dataset |
| | |
| | ```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} |
| | } |
| | ``` |
| | |
| | #### The underlying corpus WEBNLG 3.0 |
| | |
| | ```bibtex |
| | @inproceedings{castro-ferreira-etal-2020-2020, |
| | title = "The 2020 Bilingual, Bi-Directional {W}eb{NLG}+ Shared Task: Overview and Evaluation Results ({W}eb{NLG}+ 2020)", |
| | author = "Castro Ferreira, Thiago and Gardent, Claire and Ilinykh, Nikolai and van der Lee, Chris and Mille, Simon and Moussallem, Diego and Shimorina, Anastasia", |
| | booktitle = "Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)", |
| | year = "2020", |
| | pages = "55--76" |
| | } |
| | ``` |
| | |
| | |
| | |
