Enriched README

README.md

@@ -1,10 +1,4 @@
 ---
-tags:
-- qa
-- sparql
-language:
-- en
-access: private
 dataset_info:
   features:
   - name: uid
@@ -45,4 +39,183 @@ dataset_info:
     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}
+}
+```