Sparse Logistic Regression with High-order Features for Automatic Grammar Rule Extraction from Treebanks

arXiv:2403.17534v1 Announce Type: new
Abstract: Descriptive grammars are highly valuable, but writing them is time-consuming and difficult. Furthermore, while linguists typically use corpora to create them, grammar descriptions often lack quantitative data. As for formal grammars, they can be challenging to interpret. In this paper, we propose a new method to extract and explore significant fine-grained grammar patterns and potential syntactic grammar rules from treebanks, in order to create an easy-to-understand corpus-based grammar. More specifically, we extract descriptions and rules …

abstract arxiv cs.cl data extraction features grammar logistic regression paper quantitative regression them type writing