Annotation of Multi-Word Expressions in Czech Texts

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14210%2F15%3A00085165" target="_blank" >RIV/00216224:14210/15:00085165 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Annotation of Multi-Word Expressions in Czech Texts

Popis výsledku v původním jazyce

Multi-word expressions (MWEs) are difficult to define and also difficult to annotate. Some of them cause serious errors in the traditional annotation pipeline tokenization - morphological analysis - morphological disambiguation. Many cases of incorrect annotation in Czech corpora are known. To narrow the research topic, we focus only in fixed MWEs ? those with fixed word order and no ellidable components. In this paper, we propose a corpus-based method that reveals fixed MWE candidates. From the web-based corpus of Czech, we extracted 25,091 expressions, 2,140 of them were identified as MWEs, 332 as probable MWEs, and 174 of them can be either MWEs or one single word. Our method is based on corpus data observation that indicates that people are unsurewhen writing a MWE whether it is one word, a word with dashes, or several words. The result is a list of MWE candidates and also an application that classifies the input as MWE, probable MWE, or non-MWE.

Název v anglickém jazyce

Annotation of Multi-Word Expressions in Czech Texts

Popis výsledku anglicky

Multi-word expressions (MWEs) are difficult to define and also difficult to annotate. Some of them cause serious errors in the traditional annotation pipeline tokenization - morphological analysis - morphological disambiguation. Many cases of incorrect annotation in Czech corpora are known. To narrow the research topic, we focus only in fixed MWEs ? those with fixed word order and no ellidable components. In this paper, we propose a corpus-based method that reveals fixed MWE candidates. From the web-based corpus of Czech, we extracted 25,091 expressions, 2,140 of them were identified as MWEs, 332 as probable MWEs, and 174 of them can be either MWEs or one single word. Our method is based on corpus data observation that indicates that people are unsurewhen writing a MWE whether it is one word, a word with dashes, or several words. The result is a list of MWE candidates and also an application that classifies the input as MWE, probable MWE, or non-MWE.

Druh

D - Stať ve sborníku

CEP obor

AI - Jazykověda

OECD FORD obor

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Projekt

<a href="/cs/project/7F14047" target="_blank" >7F14047: Harvesting big text data for under-resourced languages</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Ninth Workshop on Recent Advances in Slavonic Natural Language Processing

ISBN

9788026309741

ISSN

2336-4289

e-ISSN

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Počet stran výsledku

10

Strana od-do

103-112

Název nakladatele

Tribun EU

Místo vydání

Brno

Místo konání akce

Karlova Studánka

Datum konání akce

1. 1. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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