Open Knowledge Graph Canonicalization

2 papers with code • 1 benchmarks • 0 datasets

Open Information Extraction approaches leads to creation of large Knowledge bases (KB) from the web. The problem with such methods is that their entities and relations are not canonicalized, which leads to storage of redundant and ambiguous facts. For example, an Open KB storing \<Barack Obama, was born in, Honolulu> and \<Obama, took birth in, Honolulu> doesn't know that Barack Obama and Obama mean the same entity. Similarly, took birth in and was born in also refer to the same relation. Problem of Open KB canonicalization involves identifying groups of equivalent entities and relations in the KB.

( Image credit: CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information )

Most implemented papers

CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information

malllabiisc/cesi 1 Feb 2019

Open Information Extraction (OpenIE) methods extract (noun phrase, relation phrase, noun phrase) triples from text, resulting in the construction of large Open Knowledge Bases (Open KBs).

COMBO: A Complete Benchmark for Open KG Canonicalization

jeffchy/combo 8 Feb 2023

The subject and object noun phrases and the relation in open KG have severe redundancy and ambiguity and need to be canonicalized.