Detailed Information on Publication Record
2017
KernelTagger – a PoS Tagger for Very Small Amount of Training Data
RYCHLÝ, PavelBasic information
Original name
KernelTagger – a PoS Tagger for Very Small Amount of Training Data
Authors
RYCHLÝ, Pavel (203 Czech Republic, guarantor, belonging to the institution)
Edition
Brno, Proceedings of the Eleventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2017, p. 107-110, 4 pp. 2017
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"
RIV identification code
RIV/00216224:14330/17:00095304
Organization unit
Faculty of Informatics
ISBN
978-80-263-1340-3
ISSN
UT WoS
000426613500012
Keywords in English
PoS tagging; morphological tagging; language model; Czech
Tags
International impact
Změněno: 8/4/2021 14:45, doc. Mgr. Pavel Rychlý, Ph.D.
Abstract
V originále
The paper describes a new Part of speech (PoS) tagger which can learn a PoS tagging language model from very short annotated text with the use of much bigger non-annotated text. Only several sentences could be used for training to achieve much better accuracy than a baseline. The results cannot be compared to the results of state-of-the-art taggers but it could be used during the annotation process for a pre-annotation.
Links
| GA15-13277S, research and development project |
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| LM2015071, research and development project |
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