Open Information Extraction Edit Task
Natural Language Processing
About
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).
Benchmarks
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Datasets
Greatest papers with code
Graphene: A Context-Preserving Open Information Extraction System
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.
Graphene: Semantically-Linked Propositions in Open Information Extraction
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.
CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information
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).
Ranked #1 on
Noun Phrase Canonicalization
on Ambiguous Dataset
FEATURE ENGINEERING NOUN PHRASE CANONICALIZATION OPEN INFORMATION EXTRACTION OPEN KNOWLEDGE GRAPH CANONICALIZATION
OPIEC: An Open Information Extraction Corpus
In this paper, we release, describe, and analyze an OIE corpus called OPIEC, which was extracted from the text of English Wikipedia.
MinIE: Minimizing Facts in Open Information Extraction
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
While traditional systems for Open Information Extraction were statistical and rule-based, recently neural models have been introduced for the task.
OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction
EMNLP 2020
• dair-iitd/openie6
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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.