Combining Grammatical and Relational Approaches. A Hybrid Method for the Identification of Candidate Collocations from Corpora
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AALQBLMBB" target="_blank" >RIV/00216208:11320/25:ALQBLMBB - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2024.mwe-1.18" target="_blank" >https://aclanthology.org/2024.mwe-1.18</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Combining Grammatical and Relational Approaches. A Hybrid Method for the Identification of Candidate Collocations from Corpora
Original language description
We present an evaluation of three different methods for the automatic identification of candidate collocations in corpora, part of a research project focused on the development of a learner dictionary of Italian collocations. We compare the commonly used POS-based method and the syntactic dependency-based method with a hybrid method integrating both approaches. We conduct a statistical analysis on a sample corpus of written and spoken texts of different registers. Results show that the hybrid method can correctly detect more candidate collocations against a human annotated benchmark. The scores are particularly high in adjectival modifier rela- tions. A hybrid approach to candidate collocation identification seems to lead to an improvement in the quality of results.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024
ISBN
978-2-493-81420-3
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
138-146
Publisher name
ELRA and ICCL
Place of publication
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Event location
Torino, Italia
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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