Open AccessLexical Factorization and Syntactic Behavior
Author(s) -
James Pustejovsky,
Aravind K. Joshi
Publication year - 2017
Publication title -
linguistic issues in language technology
Language(s) - English
Resource type - Journals
eISSN - 1945-3590
pISSN - 1945-3604
DOI - 10.33011/lilt.v15i.1407
Subject(s) - computer science , verb , sentence , natural language processing , linguistics , artificial intelligence , lexical semantics , expression (computer science) , distributional semantics , semantics (computer science) , meaning (existential) , realization (probability) , lexical definition , lexical functional grammar , lexical item , generative grammar , psychology , mathematics , semantic similarity , programming language , philosophy , statistics , psychotherapist
In this paper, we examine the correlation between lexical semantics and the syntactic realization of the different components of a word’s meaning in natural language. More specifically, we will explore the effect that lexical factorization in verb semantics has on the suppression or expression of semantic features within the sentence. Factorization was a common analytic tool employed in early generative linguistic approaches to lexical decomposition, and continues to play a role in contemporary semantics, in various guises and modified forms. Building on the unpublished analysis of verbs of seeing in Joshi (1972), we argue here that the significance of lexical factorization is twofold: first, current models of verb meaning owe much of their insight to factor-based theories of meaning; secondly, the factorization properties of a lexical item appear to influence, both directly and indirectly, the possible syntactic expressibility of arguments and adjuncts in sentence composition. We argue that this information can be used to compute what we call the factor expression likelihood (FEL) associated with a verb in a sentence. This is the likelihood that the overt syntactic expression of a factor will cooccur with the verb. This has consequences for the compositional mechanisms responsible for computing the meaning of the sentence, as well as significance in the creation of computational models attempting to capture linguistic behavior over large corpora.