Towards Revised System of Verb Wordnet Relations for Polish

A revised model for the description of verbs in plWordNet a large wordnet of Polish is presented in the paper. The model has originated from the previous one (the versions 2.0 and 3.0) as a combination of simplifications and expansions. The simplifications were motivated by the collected experience of the previous model implementation for almost 18 thousand Polish verbs. The proposed expansions are meant to improve the description of verbs and support provided by plWordNet for various applications. 1 Underestimated Wordnet Part Verbs are mostly described by fewer relations in wordnets and the verb subnetwork expresses lower density providing less information. In this paper we claim that: ● a richer structure of verb relations can be introduced into a wordnet, ● rich verb relations in a wordnet can supplement valency-based model in a way which is attractive for many applications. Our goal is to outline a model for the description of verbs in plWordNet which consists of: features (e.g. verb class, aspect) and lexico-semantic relations and is strongly based on the plWordNet general model. We are going to confine the discussion only to the Polish language and plWordNet (plWN a large wordnet for Polish [30]), but in a perspective enabling more general conclusions. The presented work builds on the previous model proposed for plWN 2.0 [28] and used also in the version 3.0 [30], as well as the experience collected from its implementation for 17,391 verb lemmas. During this work it became clear that the model must be refined in order to improve its applicability in daily wordnet editing practice and consistency of the wordnet editor decisions. Six verb relations were proposed for Princeton WordNet (PWN) [34]: synonymy, antonymy, inclusive entailment (proper inclusion), troponymy (coextensiveness), cause and presupposition. Later, since PWN 1.5, inclusion and presupposition have been combined into entailment. GermaNet identified troponymy with hyponymy [22]. PWN’s inclusive entailment was renamed subevent in EWN [1], and ‘entailment’ is only a label for presupposition (backward along the timeline) [15]. Causality is cross-categorial [23]. EWN’s set is similar to GermaNet’s [48]. Hyponymy is PWN’s troponymy. Cause includes PWN’s 1 http://plwordnet.pwr.edu.pl presupposition [47]. EWN also introduced near-synonymy (for semantically close cohyponyms), near-antonymy, as well as cross-categorial synonymy, antonymy and hypernymy. There are 19 verb relations in plWN 3.0, 6 of them have derivational origin. Table 1 contrasts our selected verb relations with those of PWN, EWN and GermaNet. A list of plWN 4.0 verb relations is presented in Table 2 and discussed in Sec. 3-4. 2 Constitutive Relations and Features 2.1 Synset Definition The plWordNet model, cf [29; 30] is based on lexical units (LUs, i.e. triples: lemma, part of speech, sense identifier) as basic building blocks. LUs are grouped into synsets on the basis of sharing constitutive relations and features, i.e. two LUs belong to one synset if and only if they share targets of the constitutive relations and values of the constitutive features. Constitutive relations are selected lexico-semantic relations that are enough frequent, express relatively high sharing factor and originate from the tradition of lexicography and wordnets and are relatively well understood, e.g. hyper/hyponymy, holo/meronymy, iterativity, distributivity. Constitutive features constrain the shape of the system of lexico-semantic relations (e.g. aspect or adjective and verb classes) or express some general pragmatic conditions on the use of lexical meanings (e.g. stylistic register). Constitutive features are often referred to in the definitions of the lexico-semantic relations, e.g. hyper/hyponymy is defined only for adjectives of the same class or inter-register synonymy links LUs of non-compatible lexical registers, cf [30]. Summing up this very brief plWN model description, see also [29], lexico-semantic relations are the main means of description. They all can be traced back to the language data. Synset relations are a kind of abbreviations representing sets of constitutive relations held between members of two synsets. The synonymy relation is to some extent derived from the constitutive relations and features that define synsets.