D 2014

Low Inter-Annotator Agreement = An Ill-Defined Problem?

KOVÁŘ, Vojtěch, Pavel RYCHLÝ and Miloš JAKUBÍČEK

Basic information

Original name

Low Inter-Annotator Agreement = An Ill-Defined Problem?

Authors

KOVÁŘ, Vojtěch (203 Czech Republic, guarantor, belonging to the institution), Pavel RYCHLÝ (203 Czech Republic, belonging to the institution) and Miloš JAKUBÍČEK (203 Czech Republic, belonging to the institution)

Edition

Brno, Eighth Workshop on Recent Advances in Slavonic Natural Language Processing, p. 57-62, 6 pp. 2014

Publisher

Tribun EU

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

RIV identification code

RIV/00216224:14330/14:00077512

Organization unit

Faculty of Informatics

ISSN

UT WoS

000374560500007

Keywords in English

NLP; inter-annotator agreement; low inter-annotator agreement; evaluation

Tags

International impact, Reviewed
Změněno: 7/6/2021 17:27, doc. Mgr. Pavel Rychlý, Ph.D.

Abstract

V originále

nnotation tasks where the inter-annotator agreement is low are usually considered ill-defined and not worth attention. Such tasks are also considered unsuitable for algorithmic solution and for evaluation of computer programs that aim at solving them. However, there is a lot of problems (not only) in the natural language processing field that are practically defined and do have this nature, and we need computer programs that are able to solve them. The paper illustrates such problems on particular examples and suggests methodology that will enable training and evaluating tools using data with low inter-annotator agreement.

Links

LM2010013, research and development project
Name: LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat (Acronym: LINDAT-Clarin)
Investor: Ministry of Education, Youth and Sports of the CR
7F14047, research and development project
Name: Harvesting big text data for under-resourced languages (Acronym: HaBiT)
Investor: Ministry of Education, Youth and Sports of the CR