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KGConv / README.md
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---
configs:
- config_name: labels
data_files: data/labels.json
- config_name: templates
data_files: data/templates.json
- config_name: conversations.country
data_files:
- path: data/country/test.json
split: test
- path: data/country/dev.json
split: dev
- path: data/country/train.json
split: train
- config_name: conversations.historical_event
data_files:
- path: data/historical_event/test.json
split: test
- path: data/historical_event/dev.json
split: dev
- path: data/historical_event/train.json
split: train
- config_name: conversations.food
data_files:
- path: data/food/test.json
split: test
- path: data/food/dev.json
split: dev
- path: data/food/train.json
split: train
- config_name: conversations.space_object
data_files:
- path: data/space_object/test.json
split: test
- config_name: conversations.with_unseen_properties
data_files:
- path: data/with_unseen_properties/test.json
split: test
- config_name: conversations.taxon
data_files:
- path: data/taxon/test.json
split: test
- config_name: conversations.person
data_files:
- path: data/person/test.json
split: test
- path: data/person/dev.json
split: dev
- path: data/person/train.json
split: train
- config_name: conversations.ideology
data_files:
- path: data/ideology/test.json
split: test
- path: data/ideology/dev.json
split: dev
- path: data/ideology/train.json
split: train
- config_name: conversations.molecular_entity
data_files:
- path: data/molecular_entity/test.json
split: test
- path: data/molecular_entity/dev.json
split: dev
- path: data/molecular_entity/train.json
split: train
---
# KGConv, a Conversational Corpus grounded in Wikidata
## Table of Contents
- [Dataset Card Creation Guide](#dataset-card-creation-guide)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Additional Information](#additional-information)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Repository:** [https://github.com/Orange-OpenSource/KGConv/]()
- **Paper:** [https://arxiv.org/abs/2308.15298]()
- **Point of Contact:** <[email protected]>, <[email protected]>, <[email protected]>, <[email protected]>
### Dataset Summary
KGConv is a large corpus of 71k english conversations where each question-answer pair is grounded in a Wikidata fact. The conversations were generated automatically: in particular, questions were created using a collection of 10,355 templates; subsequently, the naturalness of conversations was improved by inserting ellipses and coreference into questions, via both handcrafted rules and a generative rewriting model. The dataset thus provides several variants of each question (12 on average), organized into 3 levels of conversationality. KGConv can further be used for other generation and analysis tasks such as single-turn question generation from Wikidata triples, question rewriting, question answering from conversation or from knowledge graphs and quiz generation.
### Languages
English.
## Dataset Structure
The dataset has three components:
- **conversation configs**, divided in several themes that correspond to configs of the form `conversations.theme`, where theme has to be replaced by one of the following: country, food, historical_event, ideology, molecular_entity, person, space_object, taxon, with_unseen_properties;
- **labels**, a config that contains labels for all entities and properties involved in the conversations;
- **templates**, a config that contains the templates that where used for generating questions.
### Data Instances
Instance from the configs with name of the form "conversations.theme" (e.g. "conversations.country") have the following form:
```
{
"conversation_id": "69795",
"root_neighbourhood": [
[
"Q6138903",
"P106",
"Q82955"
],
[
"Q6138903",
"P19",
"Q3408680"
],
...
],
"conversation": [
{
"triple": [
"Q691",
"P30",
"Q538"
],
"question variants": [
{
"out-of-context": "In which continent is Papua New Guinea located?",
"in-context": "In which continent is Papua New Guinea located?",
"in-context subject ref": "Papua New Guinea",
"synthetic-in-context": "In which continent is Papua New Guinea located?"
},
{
"out-of-context": "In what continent is Papua New Guinea in?",
"in-context": "In what continent is Papua New Guinea in?",
"in-context subject ref": "Papua New Guinea",
"synthetic-in-context": "In what continent is Papua New Guinea in?"
},
...
],
"answer": "Oceania"
},
{
"triple": [
"Q691",
"P38",
"Q200759"
],
"question variants": [
{
"out-of-context": "What is accepted as the currency of Papua New Guinea?",
"in-context": "What is accepted as the currency of Papua New Guinea?",
"in-context subject ref": "Papua New Guinea",
"synthetic-in-context": "What is accepted as the currency?"
},
{
"out-of-context": "What is the currency of Papua New Guinea?",
"in-context": "What is the currency of Papua New Guinea?",
"in-context subject ref": "Papua New Guinea",
"synthetic-in-context": "What is the currency?"
},
...
],
"answer": "kina"
},
...
```
Instances from the `labels` config are like this:
```
{
"entity": "Q39",
"labels": [
"Swiss Confederation",
"CHE",
"Confoederatio Helvetica",
"Swiss",
"Schweiz",
"SUI",
"Switzerland",
"CH",
"Suisse",
"Svizzera"
],
"preferred_label": "Switzerland"
}
```
Instances from the `templates` config are as follows.
```
{
"template_key": {
"p": "P1201",
"s_types": [
"Q149918"
],
"o_types": []
},
"templates": [
{
"left": "what is the space tug of ",
"right": "?",
"source": "interface:automatic labeler"
},
{
"left": "what was the space tug of ",
"right": "?",
"source": "interface:624dc1cd4432b5035ba082df"
},
...
]
}
```
### Data Fields
The fields from the configs with name of the form "conversations.theme" (e.g. "conversations.country") are the following:
- `conversation`: list of dicts; each dict reprensent one question+answer and has the following fields:
- `conversation_id`: string
- `root_neighbourhood`: list of triples (each triple is itself represented by a list of 3 string elements) that constitute the neighbourhood of the conversation root entity in the knowledge graph (see the LREC publication for more details)
- `triple`: triple on which the question is based (list of three string elements)
- `question variants`: list of dict; each dict contain several forms of a question obtained via a given template (see the LREC publication for more details)
- `out-of-context`: one form of the question variant
- `in-context`: another form of the question variant
- `in-context subject ref`: how the subject is referred to in the in-context form
- `synthetic-in-context`: yet another form of the question variant
- `answer`: answer to the question (string)
The fields from the `labels` config are the following:
- `entity`: string, id of the entity
- `labels`: list of strings
- `preferred_label`: string
The fields from the `templates` config are the following:
- `template_key`: a dict containing the conditions for using the templates listed in `templates`, with the following fields:
- `p`: id of the property
- `s_types`: required types for subject
- `o_types`: require types for object
- `templates`: list of dicts representing templates; each dict has the following fields:
- `left`: left part of the template
- `right`: right part of the template
- `source`: origin of the template (string)
## Additional Information
### Licensing Information
This software is distributed under the Creative Commons Attribution 4.0 International,
the text of which is available at https://spdx.org/licenses/CC-BY-4.0.html
or see the "license.txt" file for more details.
### Citation Information
```
@article{brabant2023kgconv,
title={KGConv, a Conversational Corpus grounded in Wikidata},
author={Quentin Brabant and Gwenole Lecorve and Lina M. Rojas-Barahona and Claire Gardent},
year={2023},
eprint={2308.15298},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```