Distributional analysis of copredication: Towards distinguishing systematic polysemy from coercion
Authors: Elisabetta Jezek, Laure Vieu (Università di Pavia, CNRS, Université Toulouse III, 2014)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In this paper we argue that the account of the notion of complex type based on copredication tests is problem-atic, because copredication is possible, albeit less frequent, also with expres-sions which exhibit polysemy due to co-ercion. We show through a distributional and lexico-syntactic pattern-based corpus analysis that the variability of copredica-tion contexts is the key to distinguish com-plex types nouns from nouns subject to co-ercion.

Introduction
Copredication can be defined as a “grammatical construction in which two predicates jointly apply to the same argument” (Asher 2011, 11). We focus here on copredications in which the two predicates select for incompatible types. An example is (1): (1) Lunch was delicious but took forever. where one predicate (‘take forever’) selects for the event sense of the argument lunch while the other (‘delicious’) selects for the food sense. Polysemous expressions entering such copredication contexts are generally assumed to have a complex type (Pustejovsky 1995), that is, to lexically refer to entities “made up” of two (or more) components of a single type; it is thus assumed for example that lunch is of the complex type event food.1 Copredication as a defining criterion for linguistic expressions referring to complex types is, however, problematic, because copredication is possible, albeit less frequent, also with expressions which exhibit polysemy because of coercion, as in the case of the noun sandwich in such contexts as (2): (2) Sam grabbed and finished the sandwich in one minute. where the predicate grab selects for the simple type the noun sandwich is associated with (food), whereas finish coerces it to an event. The claim that the event sense exhibited by sandwich is coerced is supported by the low variability of event contexts in which sandwich appears (as opposed to lunch); see for example “during lunch” (780 hits for the Italian equivalent in our reference corpus, cf. section 3) vs. “*during the sandwich” (0 hits). Our goal is therefore twofold: evaluate whether at the empirical level it is possible to distinguish, among nouns appearing in copredication contexts, between complex types and simple (or complex) types subject to coercion effects; and propose a method to extract complex type nouns from corpora, combining distributional and lexicosyntactic pattern-based analyses. Our working hypothesis is that lexicalized complex types appear in copredication patterns more systematically, and so that high variability of pair of predicates in copredication contexts is evidence of complex type nouns, while low variability points to simple (or complex) type nouns subject to coercion effects. In the sections that follow, we will first raise the questions what counts as a copredication and what copredication really tell us about the underlying semantics of the nouns that support it. Then, we will introduce the experiments we conducted so far to verify our hypothesis. Finally, we will draw some conclusions and point at the experiments we have planned as future work.

Conclusion
We can therefore conclude that an experimental method to separate nouns of complex types from nouns subject to coercion appears possible. The proposed method constitutes the first attempt at semi-automatically extracting from corpus com- plex type nouns, something remaining elusive up to now. In addition, we learned that letter should be preferred over book as prototype of the com-plex type Info•Phys. In fact, this complex type is not the most straightforward since the dependence between the components of a dot object is not one-to-one. The case of Event • Food with lunch as prototype, in which there is such a tight symmetric dependence and no competition with separate sim-ple senses, might prove easier to deal with. This will be tackled in a next experiment. The predicate selection is a critical phase in the method proposed. It is difficult if not impossible to avoid polysemy and metaphorical uses, espe-cially since the relevant copredications are sparse and we cannot rely only on highly specialized un-frequent predicates. In future work, we plan to ex-periment with fully automatic selection, exploiting distributional semantics methods. Dimension re-duction through non-negative matrix factorization yields a possible interpretation of the dimensions in terms of “topics”, which is confirmed by ex-periments (Van de Cruys et al. 2011). Building on this, we shall check whether “topics” for predi-cates correspond to selectional restrictions suitable to build our copredication patterns.