Open Information Extraction

52 papers with code • 13 benchmarks • 12 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).

Most implemented papers

OPIEC: An Open Information Extraction Corpus

uma-pi1/OPIEC AKBC 2019

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

Multi-View Clustering for Open Knowledge Base Canonicalization

yang233666/cmvc 22 Jun 2022

In this paper, we propose CMVC, a novel unsupervised framework that leverages these two views of knowledge jointly for canonicalizing OKBs without the need of manually annotated labels.

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

CSJianYang/Multilingual-Multimodal-NLP 12 Aug 2023

Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages.

Relation Schema Induction using Tensor Factorization with Side Information

malllabiisc/sictf EMNLP 2016

To the best of our knowledge, this is the first application of tensor factorization for the RSI problem.