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In natural language processing, open information extraction is the task of generating a structured, machine-readable representation of the information in text, usually in the form of triples or n-ary propositions (Source: Wikipedia).

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Greatest papers with code

Graphene: A Context-Preserving Open Information Extraction System

COLING 2018 Lambda-3/Graphene

In that way, we preserve the context of the relational tuples extracted from a source sentence, generating a novel lightweight semantic representation for Open IE that enhances the expressiveness of the extracted propositions.

OPEN INFORMATION EXTRACTION

Graphene: Semantically-Linked Propositions in Open Information Extraction

COLING 2018 Lambda-3/Graphene

We present an Open Information Extraction (IE) approach that uses a two-layered transformation stage consisting of a clausal disembedding layer and a phrasal disembedding layer, together with rhetorical relation identification.

OPEN INFORMATION EXTRACTION

CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information

1 Feb 2019malllabiisc/cesi

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).

FEATURE ENGINEERING NOUN PHRASE CANONICALIZATION OPEN INFORMATION EXTRACTION OPEN KNOWLEDGE GRAPH CANONICALIZATION

OPIEC: An Open Information Extraction Corpus

28 Apr 2019uma-pi1/minie

In this paper, we release, describe, and analyze an OIE corpus called OPIEC, which was extracted from the text of English Wikipedia.

OPEN INFORMATION EXTRACTION QUESTION ANSWERING

MinIE: Minimizing Facts in Open Information Extraction

EMNLP 2017 uma-pi1/minie

The goal of Open Information Extraction (OIE) is to extract surface relations and their arguments from natural-language text in an unsupervised, domain-independent manner.

OPEN INFORMATION EXTRACTION QUESTION ANSWERING RELATION EXTRACTION

IMoJIE: Iterative Memory-Based Joint Open Information Extraction

ACL 2020 dair-iitd/imojie

While traditional systems for Open Information Extraction were statistical and rule-based, recently neural models have been introduced for the task.

OPEN INFORMATION EXTRACTION

OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction

EMNLP 2020 dair-iitd/openie6

This IGL based coordination analyzer helps our OpenIE system handle complicated coordination structures, while also establishing a new state of the art on the task of coordination analysis, with a 12. 3 pts improvement in F1 over previous analyzers.

OPEN INFORMATION EXTRACTION