Search

Multiword expressions can have both idiomatic and literal occurrences. For instance pulling strings can be understood either as making use of one’s influence, or literally. Distinguishing these two cases has been addressed in linguistics and psycholinguistics studies, and is also considered one of the major challenges in MWE processing. We suggest that literal occurrences should be considered in both semantic and syntactic terms, which motivates their study in a treebank. We propose heuristics to automatically pre-identify candidate sentences that might contain literal occurrences of verbal VMWEs, and we apply them to existing treebanks in five typologically different languages: Basque, German, Greek, Polish and Portuguese. We also perform a linguistic study of the literal occurrences extracted by the different heuristics. The results suggest that literal occurrences constitute a rare phenomenon. We also identify some properties that may distinguish them from their idiomatic counterparts. This article is a largely extended version of Savary and Cordeiro (2018).

As the nature of negative polarity items (NPIs) and their licensing contexts is still under much debate, a broad empirical basis is an important cornerstone to support further insights in this area of research. The work discussed in this paper is intended as a contribution to realizing this objective. We briefly introduce the phenomenon of NPIs and outline major theories about their licensing and also various licensing contexts before discussing our major topics: Firstly, a corpus-based retrieval method for NPI candidates is described that ranks the candidates according to their distributional dependence on the licensing contexts. Our method extracts single-word candidates and is extended to also capture multi-word candidates. The basic idea for automatically collecting NPI candidates from a large corpus is that an NPI behaves like a kind of collocate to its licensing contexts. Manual inspection and interpretation of the candidate lists identify the actual NPIs. Secondly, an online repository for NPIs and other items that show distributional idiosyncrasies is presented, which offers an empirical database for further (theoretical) research on these items in a sustainable way.

Our paper aims at capturing the distribution of negative polarity items (NPIs) within lexicalized Tree Adjoining Grammar (LTAG). The condition under which an NPI can occur in a sentence is for it to be in the scope of a negation with no quantifiers scopally intervening. We model this restriction within a recent framework for LTAG semantics based on semantic unification. The proposed analysis provides features that signal the presence of a negation in the semantics and that specify its scope. We extend our analysis to modelling the interaction of NPI licensing and neg raising constructions.

In this paper, we present an open-source parsing environment (Tuebingen Linguistic Parsing Architecture, TuLiPA) which uses Range Concatenation Grammar (RCG) as a pivot formalism, thus opening the way to the parsing of several mildly context-sensitive formalisms. This environment currently supports tree-based grammars (namely Tree-Adjoining Grammars, TAG) and Multi-Component Tree-Adjoining Grammars with Tree Tuples (TT-MCTAG)) and allows computation not only of syntactic structures, but also of the corresponding semantic representations. It is used for the development of a tree-based grammar for German., Comment: Dans 2nd Workshop on Grammar Engineering Across Frameworks, GEAF 2008 (2008)

Richter, Frank, Manfred Sailer, and Beata Trawinski. 2010. The collection of distributionally idiosyncratic items: An interface between data and theory. In Corpora, web and databases: Computer-based methods in modern phraseology and lexicography, eds. Stefaniya Ptashnyk, Erla Hallsteinsdottir, and Noah Bubenhofer. Vol. 25 of Phraseologie und Paromiologie, 247–262. Baltmannsweiler: Schneider Verlag Hohengehren.

This chapter contributes a general overview and discussion of lexical encoding formats for multi-word expressions (MWEs) that can be used in NLP systems, in particular with large-scale grammars. The presentation is kept general in the sense that we will try to elicit basic aspects of lexical encoding and then elaborate on the specific sorts of challenges encountered when dealing with MWEs, especially the ``irregular'' regularities mentioned in the title. These insights will eventually be used to classify and evaluate different approaches to encoding. Even though this kind of evaluation cannot be conclusive given the diversity of languages and tastes, we will nevertheless argue in favor of fully flexible encoding formats exemplified with PATR-II and XMG, as opposed to the fixed encoding formats of DuELME and Walenty.