Combining Grammatical and Relational Approaches. A Hybrid Method for the Identification of Candidate Collocations from Corpora

Damiano Perri, Irene Fioravanti, Osvaldo Gervasi, Stefania Spina

Abstract
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.
Anthology ID:
2024.mwe-1.18
Volume:
Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Archna Bhatia, Gosse Bouma, A. Seza Doğruöz, Kilian Evang, Marcos Garcia, Voula Giouli, Lifeng Han, Joakim Nivre, Alexandre Rademaker
Venues:
MWE | UDW | WS
SIGs:
SIGLEX | SIGPARSE
Publisher:
ELRA and ICCL
Note:
Pages:
138–146
Language:
URL:
https://aclanthology.org/2024.mwe-1.18
DOI:
Bibkey:
Cite (ACL):
Damiano Perri, Irene Fioravanti, Osvaldo Gervasi, and Stefania Spina. 2024. Combining Grammatical and Relational Approaches. A Hybrid Method for the Identification of Candidate Collocations from Corpora. In Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024, pages 138–146, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Combining Grammatical and Relational Approaches. A Hybrid Method for the Identification of Candidate Collocations from Corpora (Perri et al., MWE-UDW-WS 2024)
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