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Open Information Extraction

16 papers with code · Natural Language Processing

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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 OPEN INFORMATION EXTRACTION OPEN KNOWLEDGE GRAPH CANONICALIZATION

A Consolidated Open Knowledge Representation for Multiple Texts

WS 2017 vered1986/OKR

We propose to move from Open Information Extraction (OIE) ahead to Open Knowledge Representation (OKR), aiming to represent information conveyed jointly in a set of texts in an open text-based manner.

OPEN INFORMATION EXTRACTION

Integrating Local Context and Global Cohesiveness for Open Information Extraction

26 Apr 2018GentleZhu/ReMine

However, current Open IE systems focus on modeling local context information in a sentence to extract relation tuples, while ignoring the fact that global statistics in a large corpus can be collectively leveraged to identify high-quality sentence-level extractions.

OPEN INFORMATION EXTRACTION

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

Answering Complex Questions Using Open Information Extraction

ACL 2017 allenai/semanticilp

While there has been substantial progress in factoid question-answering (QA), answering complex questions remains challenging, typically requiring both a large body of knowledge and inference techniques.

OPEN INFORMATION EXTRACTION QUESTION ANSWERING

Quantifying Similarity between Relations with Fact Distribution

ACL 2019 thunlp/relation-similarity

We introduce a conceptually simple and effective method to quantify the similarity between relations in knowledge bases.

OPEN INFORMATION EXTRACTION