Detecting Collocations Similarity via Logical-Linguistic Model
Nina Khairova, Svitlana Petrasova, Orken Mamyrbayev, Kuralay Mukhsina
Abstract
Semantic similarity between collocations, along with words similarity, is one of the main issues of NLP, which must be addressed, in particular, in order to facilitate the automatic thesaurus generation. In the paper, we consider the logical-linguistic model that allows defining the relation of semantic similarity of collocations via the logical-algebraic equations. We provide the model for English, Ukrainian and Russian text corpora. The implementation for each language is slightly different in the equations of the finite predicates algebra and used linguistic resources. As a dataset for our experiment, we use 5801 pairs of sentences of Microsoft Research Paraphrase Corpus for English and more than 1 000 texts of scientific papers for Russian and Ukrainian.- Anthology ID:
- W19-0802
- Volume:
- RELATIONS - Workshop on meaning relations between phrases and sentences
- Month:
- May
- Year:
- 2019
- Address:
- Gothenburg, Sweden
- Editors:
- Venelin Kovatchev, Darina Gold, Torsten Zesch
- Venue:
- IWCS
- SIG:
- SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/W19-0802
- DOI:
- 10.18653/v1/W19-0802
- Cite (ACL):
- Nina Khairova, Svitlana Petrasova, Orken Mamyrbayev, and Kuralay Mukhsina. 2019. Detecting Collocations Similarity via Logical-Linguistic Model. In RELATIONS - Workshop on meaning relations between phrases and sentences, Gothenburg, Sweden. Association for Computational Linguistics.
- Cite (Informal):
- Detecting Collocations Similarity via Logical-Linguistic Model (Khairova et al., IWCS 2019)
- PDF:
- https://preview.aclanthology.org/naacl24-info/W19-0802.pdf