Enriched README

README.md

@@ -1,6 +1,4 @@
 ---
-language:
-- en
 dataset_info:
   features:
   - name: original_nl_question
@@ -41,6 +39,177 @@ dataset_info:
     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 
+# 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}
+}
+
+```