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--- |
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license: cc-by-sa-4.0 |
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dataset_info: |
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features: |
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- name: category |
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dtype: string |
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- name: size |
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dtype: int32 |
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- name: id |
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dtype: string |
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- name: eid |
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dtype: string |
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- name: original_triple_sets |
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list: |
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- name: subject |
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dtype: string |
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- name: property |
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dtype: string |
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- name: object |
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dtype: string |
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- name: modified_triple_sets |
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list: |
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- name: subject |
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dtype: string |
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- name: property |
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dtype: string |
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- name: object |
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dtype: string |
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- name: shape |
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dtype: string |
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- name: shape_type |
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dtype: string |
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- name: lex |
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sequence: |
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- name: comment |
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dtype: string |
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- name: lid |
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dtype: string |
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- name: text |
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dtype: string |
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- name: lang |
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dtype: string |
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- name: test_category |
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dtype: string |
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- name: dbpedia_links |
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sequence: string |
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- name: links |
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sequence: string |
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- name: graph |
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list: |
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list: string |
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- name: main_entity |
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dtype: string |
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- name: mappings |
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list: |
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- name: modified |
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dtype: string |
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- name: readable |
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dtype: string |
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- name: graph |
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dtype: string |
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- name: dialogue |
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list: |
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- name: question |
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list: |
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- name: source |
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dtype: string |
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- name: text |
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dtype: string |
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- name: graph_query |
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dtype: string |
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- name: readable_query |
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dtype: string |
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- name: graph_answer |
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list: string |
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- name: readable_answer |
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list: string |
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- name: type |
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list: string |
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splits: |
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- name: train |
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num_bytes: 33200723 |
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num_examples: 10016 |
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- name: validation |
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num_bytes: 4196972 |
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num_examples: 1264 |
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- name: test |
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num_bytes: 4990595 |
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num_examples: 1417 |
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- name: challenge |
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num_bytes: 420551 |
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num_examples: 100 |
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download_size: 9637685 |
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dataset_size: 42808841 |
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task_categories: |
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- conversational |
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- question-answering |
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- text-generation |
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tags: |
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- qa |
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- knowledge-graph |
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- sparql |
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language: |
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- en |
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--- |
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# Dataset Card for WEBNLG-QA |
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## Dataset Description |
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- **Paper:** [SPARQL-to-Text Question Generation for Knowledge-Based Conversational Applications (AACL-IJCNLP 2022)](https://aclanthology.org/2022.aacl-main.11/) |
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- **Point of Contact:** Gwénolé Lecorvé |
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### Dataset Summary |
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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. |
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### Supported tasks |
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* Knowledge-based question-answering |
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* SPARQL-to-Text conversion |
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#### Knowledge based question-answering |
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Below is an example of dialogue: |
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- Q1: What is used as an instrument is Sludge Metal or in Post-metal? |
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- A1: Singing, Synthesizer |
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- Q2: And what about Sludge Metal in particular? |
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- A2: Singing |
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- Q3: Does the Year of No Light album Nord belong to this genre? |
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- A3: Yes. |
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#### SPARQL-to-Text Question Generation |
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SPARQL-to-Text question generation refers to the task of converting a SPARQL query into a natural language question, eg: |
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```SQL |
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SELECT (COUNT(?country) as ?answer) |
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WHERE { ?country property:member_of resource:Europe . |
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?country property:population ?n . |
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FILTER ( ?n > 10000000 ) |
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} |
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``` |
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could be converted into: |
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```txt |
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How many European countries have more than 10 million inhabitants? |
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``` |
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## Dataset Structure |
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### Types of questions |
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Comparison of question types compared to related datasets: |
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| | | [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) | |
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|--------------------------|-----------------|:---------------:|:------:|:-----------:|:----:|:---------:| |
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| **Number of triplets in query** | 1 | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | 2 | | ✓ | ✓ | ✓ | ✓ | |
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| | More | | | ✓ | ✓ | ✓ | |
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| **Logical connector between triplets** | Conjunction | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | Disjunction | | | | ✓ | ✓ | |
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| | Exclusion | | | | ✓ | ✓ | |
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| **Topology of the query graph** | Direct | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | Sibling | | ✓ | ✓ | ✓ | ✓ | |
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| | Chain | | ✓ | ✓ | ✓ | ✓ | |
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| | Mixed | | | ✓ | | ✓ | |
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| | Other | | ✓ | ✓ | ✓ | ✓ | |
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| **Variable typing in the query** | None | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | Target variable | | ✓ | ✓ | ✓ | ✓ | |
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| | Internal variable | | ✓ | ✓ | ✓ | ✓ | |
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| **Comparisons clauses** | None | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | String | | | ✓ | | ✓ | |
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| | Number | | | ✓ | ✓ | ✓ | |
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| | Date | | | ✓ | | ✓ | |
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| **Superlative clauses** | No | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | Yes | | | | ✓ | | |
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| **Answer type** | Entity (open) | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | Entity (closed) | | | | ✓ | ✓ | |
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| | Number | | | ✓ | ✓ | ✓ | |
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| | Boolean | | ✓ | ✓ | ✓ | ✓ | |
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| **Answer cardinality** | 0 (unanswerable) | | | ✓ | | ✓ | |
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| | 1 | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | More | | ✓ | ✓ | ✓ | ✓ | |
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| **Number of target variables** | 0 (⇒ ASK verb) | | ✓ | ✓ | ✓ | ✓ | |
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| | 1 | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | 2 | | | ✓ | | ✓ | |
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| **Dialogue context** | Self-sufficient | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | Coreference | | | | ✓ | ✓ | |
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| | Ellipsis | | | | ✓ | ✓ | |
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| **Meaning** | Meaningful | ✓ | ✓ | ✓ | ✓ | ✓ | |
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| | Non-sense | | | | | ✓ | |
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### Data splits |
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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. |
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| | Train | Validation | Test | Challenge | |
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| --------------------- | ---------- | ---------- | ---------- | ------------ | |
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| Questions | 27727 | 3485 | 4179 | 332 | |
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| Dialogues | 1001 | 1264 | 1417 | 100 | |
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| NL question per query | 0 | 0 | 0 | 2 | |
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| Characters per query | 129 (± 43) | 131 (± 45) | 122 (± 45) | 113 (± 38) | |
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| Tokens per question | - | - | - | 8.4 (± 4.5) | |
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## Additional information |
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### Related datasets |
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This corpus is part of a set of 5 datasets released for SPARQL-to-Text generation, namely: |
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- Non conversational datasets |
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- [SimpleQuestions](https://huggingface.co/datasets/OrangeInnov/simplequestions-sparqltotext) (from https://github.com/askplatypus/wikidata-simplequestions) |
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- [ParaQA](https://huggingface.co/datasets/OrangeInnov/paraqa-sparqltotext) (from https://github.com/barshana-banerjee/ParaQA) |
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- [LC-QuAD 2.0](https://huggingface.co/datasets/OrangeInnov/lcquad_2.0-sparqltotext) (from http://lc-quad.sda.tech/) |
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- Conversational datasets |
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- [CSQA](https://huggingface.co/datasets/OrangeInnov/csqa-sparqltotext) (from https://amritasaha1812.github.io/CSQA/) |
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- [WebNLQ-QA](https://huggingface.co/datasets/OrangeInnov/webnlg-qa) (derived from https://gitlab.com/shimorina/webnlg-dataset/-/tree/master/release_v3.0) |
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### Licencing information |
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* Content from original dataset: CC-BY-SA 4.0 |
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* New content: CC BY-SA 4.0 |
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### Citation information |
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#### This dataset |
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```bibtex |
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@inproceedings{lecorve2022sparql2text, |
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title={SPARQL-to-Text Question Generation for Knowledge-Based Conversational Applications}, |
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author={Lecorv\'e, Gw\'enol\'e and Veyret, Morgan and Brabant, Quentin and Rojas-Barahona, Lina M.}, |
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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)}, |
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year={2022} |
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} |
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``` |
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#### The underlying corpus WEBNLG 3.0 |
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```bibtex |
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@inproceedings{castro-ferreira-etal-2020-2020, |
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title = "The 2020 Bilingual, Bi-Directional {W}eb{NLG}+ Shared Task: Overview and Evaluation Results ({W}eb{NLG}+ 2020)", |
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author = "Castro Ferreira, Thiago and Gardent, Claire and Ilinykh, Nikolai and van der Lee, Chris and Mille, Simon and Moussallem, Diego and Shimorina, Anastasia", |
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booktitle = "Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)", |
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year = "2020", |
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pages = "55--76" |
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} |
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``` |
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