Extracting Complex Information from Natural Language Text: A Survey - IMT - Institut Mines-Télécom Access content directly
Other Publications CEUR Workshop Proceedings Year : 2020

Extracting Complex Information from Natural Language Text: A Survey

Abstract

Information Extraction is the art of extracting structured information from natural language text, and it has come a long way in recent years. Many systems focus on binary relationships between two entities-a subject and an object. However, most natural language text contains complex information such as beliefs, causality, anteriority, or relationships that span several sentences. In this paper, we survey existing approaches at this frontier, and outline promising directions of future work.
Fichier principal
Vignette du fichier
semantic-journalism-2020.pdf (762.12 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03102913 , version 1 (07-01-2021)

Identifiers

  • HAL Id : hal-03102913 , version 1

Cite

Emna Mechket, Fabian Suchanek. Extracting Complex Information from Natural Language Text: A Survey. Workshop on Semantic and knowledge graph advances for journalism, 2020. ⟨hal-03102913⟩
114 View
136 Download

Share

Gmail Facebook Twitter LinkedIn More