POS Tagging of Hungarian with Combined Statistical and Rule-Based Methods

Autor:	András Hócza, János Csirik, András Kuba
Rok vydání:	2004
Předmět:	Set (abstract data type) Parsing business.industry Computer science Key (cryptography) Rule-based system Artificial intelligence Computational linguistics computer.software_genre business computer Natural language processing Natural language
Zdroj:	Text, Speech and Dialogue ISBN: 9783540230496 TSD
DOI:	10.1007/978-3-540-30120-2_15
Popis:	In this paper we will survey the key results achieved so far in Hungarian POS tagging. The most successful approaches have been selected and re-evaluated on a manually annotated corpus containing 1.2 million words. Tests were performed on single-domain, multiple domain and cross-domain test settings. We investigate here the possibilities of further improvement of the selected POS tagging methods by combining them. Our aim is to build a POS tagger that achieves good results on a fine tag set of more than 1000 tags.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bed634fe96fe6373c3910fe8b10701c3 https://doi.org/10.1007/978-3-540-30120-2_15 Zobrazit plný text záznamu