Quasimodo / README.md
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metadata
annotations_creators:
  - machine-generated
language:
  - en
language_creators:
  - machine-generated
license:
  - cc-by-2.0
multilinguality:
  - monolingual
pretty_name: Quasimodo
size_categories:
  - 100M<n<1B
source_datasets:
  - original
tags:
  - knowledge base
  - commonsense
task_categories:
  - question-answering
task_ids:
  - closed-domain-qa

Dataset Card for Quasimodo

Table of Contents

Dataset Description

Dataset Summary

A commonsense knowledge base constructed automatically from question-answering forums and query logs.

Supported Tasks and Leaderboards

Can be useful for tasks requiring external knowledge such as question answering.

Languages

English

Dataset Structure

Data Instances

{
  "subject": "elephant",
  "predicate": "has_body_part"
  "object": "trunk",
  "modality": "TBC[so long trunks] x#x2 // TBC[long trunks] x#x9 // TBC[big trunks] x#x6 // TBC[long trunk] x#x1 // TBC[such big trunks] x#x1	0	0.9999667967035647	elephants have trunks x#x34 x#xGoogle Autocomplete, Bing Autocomplete, Yahoo Questions, Answers.com Questions, Reddit Questions // a elephants have trunks x#x2 x#xGoogle Autocomplete // a elephant have a trunk x#x2 x#xGoogle Autocomplete // elephants have so long trunks x#x2 x#xGoogle Autocomplete // elephants have long trunks x#x8 x#xGoogle Autocomplete, Yahoo Questions, Answers.com Questions // elephants have big trunks x#x6 x#xGoogle Autocomplete, Answers.com Questions, Reddit Questions // elephants have trunk x#x3 x#xGoogle Autocomplete, Yahoo Questions // elephant have long trunks x#x1 x#xGoogle Autocomplete // elephant has a trunk x#x1 x#xGoogle Autocomplete // elephants have a trunk x#x2 x#xAnswers.com Questions // an elephant has a long trunk x#x1 x#xAnswers.com Questions // elephant have trunks x#x1 x#xAnswers.com Questions // elephants have such big trunks x#x1 x#xReddit Questions",
  "score": 0.9999667967668732,
  "local_sigma": 1.0
}

Data Fields

  • subject: The subject of the triple
  • predicate: The predicate of the triple
  • object: The object of the triple
  • modality: Modalities associated with the triples with their counts. TBC means the object can be further refined to the listed objects
  • is_negative: 1 if the statement was negated
  • score: salience score of the supervised scoring model
  • local sigma: strict conditional probability of observing a (predicate, object) with a specific subject. I.e., a measure of how unique a statement is. E.g., local_sigma(lawyers, defend, serial_killers) = 1, local_sigma(lawyers, make, money) = 0.01, even though both statements have a similar score of 0.99.

Dataset Creation

See original paper.

Additional Information

Licensing Information

CC-BY 2.0

Citation Information

Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019