Combining dependency parsing and a lexical network based on lexical functions for the identification of collocations

Abstract

A collocation is a type of multiword expression formed by two parts: a base and a collocate. Usually, in a collocation, the base has a denotative or literal meaning, while the collocate has a connotative meaning. Examples of collocations: pay attention, easy as pie, strongly condemn, lend support, etc. The Meaning-Text Theory created the lexical functions to, among other objectives, represent the meaning existing between the base and the collocate or to represent the relation between the base and a support verb. For example, the lexical function Magn represents the meaning intensification, while the lexical function Caus, applied to a base, returns the support verb that represents the causality of the action expressed in the collocation. In a dependency parsing, each word (dependent) is directly associated with its governor in a phrase. In this paper, we show how we combine dependency parsing to extract collocation candidates and a lexical network based on lexical functions to identify the true collocations from the candidates. The candidates are extracted from a French corpus according to 14 dependency relations. The collocations identified are classified according to the semantic group of the lexical functions modeling them. We obtained a general precision (for all dependency types) of 76.3%, with a precision higher than 95% for collocations having certain dependency relations. We also found that about 86% of collocations identified belong to only four semantic categories: qualification, support verb, location and action/event.