How Large Are Lions? Inducing Distributions over Quantitative Attributes

Elazar, Yanai; Mahabal, Abhijit; Ramachandran, Deepak; Bedrax-Weiss, Tania; Roth, Dan

doi:10.48550/arxiv.1906.01327

Cited by 1 publication

(2 citation statements)

References 18 publications

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“…Besides qualifiers, it might be of use to include relations that are currently missing, like typical properties of concepts (e.g., elephants are heavy), or their symbolism (e.g., red is a symbol of danger). The actual information could be extracted from unstructured sources, like Wikipedia, or reused from previous extractions [7].…”

Section: Missing Knowledge Typesmentioning

confidence: 99%

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Commonsense Knowledge in Wikidata

Ilievski,

Szekely,

Schwabe

2020

Preprint

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Wikidata and Wikipedia have been proven useful for reasoning in natural language applications, like question answering or entity linking. Yet, no existing work has studied the potential of Wikidata for commonsense reasoning. This paper investigates whether Wikidata contains commonsense knowledge which is complementary to existing commonsense sources. Starting from a definition of common sense, we devise three guiding principles, and apply them to generate a commonsense subgraph of Wikidata (Wikidata-CS ). Within our approach, we map the relations of Wikidata to ConceptNet, which we also leverage to integrate Wikidata-CS into an existing consolidated commonsense graph. Our experiments reveal that: 1) albeit Wikidata-CS represents a small portion of Wikidata, it is an indicator that Wikidata contains relevant commonsense knowledge, which can be mapped to 15 ConceptNet relations; 2) the overlap between Wikidata-CS and other commonsense sources is low, motivating the value of knowledge integration; 3) Wikidata-CS has been evolving over time at a slightly slower rate compared to the overall Wikidata, indicating a possible lack of focus on commonsense knowledge. Based on these findings, we propose three recommended actions to improve the coverage and quality of Wikidata-CS further.

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Section: Missing Knowledge Typesmentioning

confidence: 99%

“…https://github.com/commonsense/conceptnet5/wiki/Downloads 6 In the future, we intend to consolidate the remaining statements of Wikidata by mapping them to ConceptNet relations as well 7. For some ConceptNet relations, like /r/PartOf and /r/HasProperty, a similar proposal to add detail comes from WebChild[27].…”

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confidence: 99%