Skip to Main content Skip to Navigation
Other publications

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.
Document type :
Other publications
Complete list of metadata

https://hal-imt.archives-ouvertes.fr/hal-03102913
Contributor : Fabian Suchanek <>
Submitted on : Thursday, January 7, 2021 - 6:33:19 PM
Last modification on : Monday, March 1, 2021 - 10:16:24 AM
Long-term archiving on: : Thursday, April 8, 2021 - 7:53:25 PM

File

semantic-journalism-2020.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03102913, version 1

Collections

Citation

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⟩

Share

Metrics

Record views

25

Files downloads

9