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natural-language-processing-8

Open Information Extraction

3260 papers • 126 benchmarks • 313 datasets

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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Benchmarks

These leaderboards are used to track progress in open-information-extraction-8

Trend

Dataset

Best Model

Actions

CaRB

CaRB

WiRe57

WiRe57

OIE2016

OIE2016

Libraries

i

Use these libraries to find open-information-extraction-8 models and implementations

Datasets

Penn Treebank

New York Times Annotated Corpus

New York Times Annotated Corpus

QA-SRL

CaRB

OIE2016

GenericsKB

Subtasks

Event Extraction

Most implemented papers

OPIEC: An Open Information Extraction Corpus

Samuel Broscheit, Kiril Gashteovski, Rainer Gemulla, Sebastian Wanner, S. Hertling•Sat Apr 27 2019

It is found that most of the facts between entities present in OPIEC cannot be found in DBpedia and/or YAGO, that OIE facts often differ in the level of specificity compared to knowledge base facts, and that Oie open relations are generally highly polysemous.

43

Content

Introduction Benchmarks Datasets Subtasks Libraries Papers

BenchIE

BenchIE

LSOIE-wiki

LSOIE-wiki

LSOIE

LSOIE

Web

Web

NYT

NYT

Penn Treebank

Penn Treebank

DocOIE-healthcare

DocOIE-healthcare

DocOIE-transportation

DocOIE-transportation

CaRB OIE benchmark (Greek Use-case)

CaRB OIE benchmark (Greek Use-case)

OpenIE

OpenIE

OPIEC

LSOIE

WiRe57

hasPart KB

0

Demonyms and Compound Relational Nouns in Nominal Open IE

Mausam, Harinder Pal•Tue May 31 2016

This work substantially improves the quality of Open IE from compound noun phrases by focusing on phenomena like demonyms and compound relational nouns.

95 0

Creating a Large Benchmark for Open Information Extraction

Gabriel Stanovsky, Ido Dagan•Mon Oct 31 2016

This work develops a methodology that leverages the recent QA-SRL annotation to create a first independent and large scale Open IE annotation and uses it to automatically compare the most prominent Open IE systems.

146 0

Multi-View Clustering for Open Knowledge Base Canonicalization

Yinan Liu, Wei Shen, Yang Yang•Tue Jun 21 2022

CMVC is proposed, a novel unsupervised framework that leverages two views of knowledge jointly for canonicalizing OKBs without the need of manually annotated labels and demonstrates the superiority of the framework through extensive experiments on multiple real-world OKB data sets against state-of-the-art methods.

13 0

MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction

Yuwei Yin, Hongcheng Guo, Jiaheng Liu, Zixiang Wang, Linzheng Chai, Jiaqi Bai, Tongliang Li, Liqun Yang, Hebboul Zine el-abidine, Zhoujun Li•Fri Aug 11 2023

An effective multi-stage tuning framework called MT4CrossIE, designed for enhancing cross-lingual open information extraction by injecting language-specific knowledge into the shared model, is proposed.

6 0

The Stanford CoreNLP Natural Language Processing Toolkit

Christopher D. Manning, M. Surdeanu, Steven Bethard, John Bauer, J. Finkel, David McClosky•Sat May 31 2014

The design and use of the Stanford CoreNLP toolkit is described, an extensible pipeline that provides core natural language analysis, and it is suggested that this follows from a simple, approachable design, straightforward interfaces, the inclusion of robust and good quality analysis components, and not requiring use of a large amount of associated baggage.

7550 0

Relation Schema Induction using Tensor Factorization with Side Information

Partha P. Talukdar, M. Nimishakavi, Uday Singh Saini•Wed May 11 2016

This paper proposes Schema Induction using Coupled Tensor Factorization (SICTF), a novel tensor factorization method for relation schema induction that factorizes Open Information Extraction triples extracted from a domain corpus along with additional side information in a principled way to induce relation schemas.

28 0

Knowledge-Guided Linguistic Rewrites for Inference Rule Verification

Prachi Jain, Mausam•Tue May 31 2016

This work investigates knowledge-guided linguistic rewrites as a secondary source of evidence and finds that they can vastly improve the quality of inference rule corpora, obtaining 27 to 33 point precision improvement while retaining substantial recall.

9 0

Porting an Open Information Extraction System from English to German

Gabriel Stanovsky, Ido Dagan, Iryna Gurevych, Tobias Falke•Mon Oct 31 2016

This paper presents a straightforward approach for adapting PropS, a rule-based predicate-argument analysis for English, to a new language, German, and obtains an Open IE system for German covering 89% of the English rule set.

18 0

Adding a benchmark result helps the community track progress.

Open Information Extraction | State-of-the-Art