Learning to detect english and hungarian light verb constructions

Abstract

Light verb constructions consist of a verbal and a nominal component, where the noun preserves its original meaning while the verb has lost it (to some degree). They are syntactically flexible and their meaning can only be partially computed on the basis of the meaning of their parts, thus they require special treatment in natural language processing. For this purpose, the first step is to identify light verb constructions.In this study, we present our conditional random fields-based tool-called FXTagger-for identifying light verb constructions. The flexibility of the tool is demonstrated on two, typologically different, languages, namely, English and Hungarian. As earlier studies labeled different linguistic phenomena as light verb constructions, we first present a linguistics-based classification of light verb constructions and then show that FXTagger is able to identify different classes of light verb constructions in both languages.Different types of texts may contain different types of light verb constructions; moreover, the frequency of light verb constructions may differ from domain to domain. Hence we focus on the portability of models trained on different corpora, and we also investigate the effect of simple domain adaptation techniques to reduce the gap between the domains. Our results show that in spite of domain specificities, out-domain data can also contribute to the successful LVC detection in all domains.

A Transition-Based System for Joint Lexical and Syntactic Analysis

“…Past research has explored either pipeline or joint approaches. Pipeline strategies consist in positioning the MWE recognition either before or after the parser itself, as in Nivre and Nilsson (2004), Eryigit et al (2011), Constant et al (2013), and Kong et al (2014) for pre-identification and as in Vincze et al (2013a) for post-identification. Joint strategies have mainly consisted in using off-the-shelf parsers and integrating MWE annotation in the syntactic structure, so that MWE identification is blind for the parser (Nivre and Nilsson, 2004;Eryigit et al, 2011;Vincze et al, 2013b;Candito and Constant, 2014;Nasr et al, 2015).…”

“…To the best of our knowledge, this system is the first transition-based parser that includes a specific mechanism for handling MWEs in two dimensions. Previous related research has usually proposed either pipeline approaches with MWE identification performed either before or after dependency parsing (Kong et al, 2014;Vincze et al, 2013a) or workaround joint solutions using off-the-shelf parsers trained on dependency treebanks where MWEs are annotated by specific subtrees (Nivre and Nilsson, 2004;Eryigit et al, 2011;Vincze et al, 2013b;Candito and Constant, 2014;Nasr et al, 2015).…”

VPCTagger: Detecting Verb-Particle Constructions With Syntax-Based Methods

“…Their method relied on a syntactic treebank, an MWE list and a morphological analyzer. Vincze et al (2013) employed a dependency parser for identifying light verb constructions in Hungarian texts as a "side effect" of parsing sentences and report state-of-the-art results for this task.…”

Predicting Dialect Variation in Immigrant Contexts Using Light Verb Constructions

“…In both cases, the meaning of the verbal complement is bleached out and the nominal complement weighs heavier than the verbal one. We will not dwell further on this subtle distinction, but we plan future work on this topic following Cook et al (2007) and Vincze et al (2013). …”