metadata

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

Dataset Card Creation Guide

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

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}
}

Datasets:

Orange
/

KGConv