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

Research output: Contribution to journal › Conference article › peer-review

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.

Original language	English
Journal	CEUR Workshop Proceedings
Volume	2699
Publication status	Published - 1 Jan 2020
Event	2020 International Conference on Information and Knowledge Management Workshops, CIKMW 2020 - Galway, Ireland Duration: 19 Oct 2020 → 23 Oct 2020

Keywords

Complex Information
Information Extraction
Semanting parsing

Cite this

@article{e9a08e63008348289758af71ed76e236,

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.",

keywords = "Complex Information, Information Extraction, Semanting parsing",

author = "Mahouachi, \{Mechket Emna\} and Fabian Suchanek",

note = "Publisher Copyright: {\textcopyright} 2020 CEUR-WS. All rights reserved.; 2020 International Conference on Information and Knowledge Management Workshops, CIKMW 2020 ; Conference date: 19-10-2020 Through 23-10-2020",

year = "2020",

month = jan,

day = "1",

language = "English",

volume = "2699",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

}

TY - JOUR

T1 - Extracting complex information from natural language text

T2 - 2020 International Conference on Information and Knowledge Management Workshops, CIKMW 2020

AU - Mahouachi, Mechket Emna

AU - Suchanek, Fabian

PY - 2020/1/1

Y1 - 2020/1/1

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.

KW - Complex Information

KW - Information Extraction

KW - Semanting parsing

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

Abstract

Keywords

Fingerprint

Cite this