COLING 2024main1 citations
A Generative Model for Lambek Categorial Sequents
Abstract
In this work, we introduce a generative model, PLC+, for generating Lambek Categorial Grammar(LCG) sequents. We also introduce a simple method to numerically estimate the model’s parameters from an annotated corpus. Then we compare our model with probabilistic context-free grammars (PCFGs) and show that PLC+ simultaneously assigns a higher probability to a common corpus, and has greater coverage.
BibTeX
@inproceedings{zhao-penn-2024-generative,
title = "A Generative Model for {L}ambek Categorial Sequents",
author = "Zhao, Jinman and
Penn, Gerald",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.50/",
pages = "584--593"
}