Extracting complex information from natural language text: A survey

Mechket Emna Mahouachi; Fabian Suchanek

Extracting complex information from natural language text: A survey

Mechket Emna Mahouachi
, Fabian Suchanek

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

Résumé

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.

langue originale	Anglais
journal	CEUR Workshop Proceedings
Volume	2699
état	Publié - 1 janv. 2020
Evénement	2020 International Conference on Information and Knowledge Management Workshops, CIKMW 2020 - Galway, Irlande Durée: 19 oct. 2020 → 23 oct. 2020

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title = "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.",

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N2 - 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.

AB - 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.

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KW - Information Extraction

KW - Semanting parsing

UR - https://www.scopus.com/pages/publications/85097567542

M3 - Conference article

AN - SCOPUS:85097567542

SN - 1613-0073

VL - 2699

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 19 October 2020 through 23 October 2020

ER -

Extracting complex information from natural language text: A survey

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