New Polysemy Structures in Wordnets Induced by Vertical Polysemy (2019)

Abstract: This paper aims to study auto-hyponymy and auto-troponymy relations (or vertical polysemy) in 11 wordnets uploaded into the new Open Multilingual Wordnet (OMW) webpage. We investigate how vertical polysemy forms polysemy structures (or sense clusters) in semantic hierarchies of the wordnets. Our main results and discoveries are new polysemy structures that have not previously been associated with vertical polysemy, along with some inconsistencies of semantic relations analysis in the studied wordnets, which should not be there. In the case study, we turn attention to polysemy structures in the Estonian Wordnet (version 2.2.0), analyzing them and giving the lexicographers comments. In addition, we describe the detection algorithm of polysemy structures and an overview of the state of polysemy structures in 11 wordnets.

## introduction the advantages of wordnet @xcite come from its specific design. on the one hand, it is a machine-readable dictionary, with definitions and examples of concepts, but on the other, a network of concepts in semantic relations @xcite . this kind of resource makes it easy to figure out how close or far concepts are semantically from each other (semantic distance). similarly, we can find the sub-concepts, super-concepts or synonyms of a given term. wordnet offers a lexicalsemantic background knowledge base for solving various nlp tasks, in particular for tasks that require semantic analysis. however, one of the problems that can make wordnet usage difficult is the lexical polysemy in its semantic hierarchies @xcite . furthermore, the problem is even more acute in the cases of polysemy where the context of two or more lemmas with the same spelling in a semantic network is barely distinguishable. the emergence of such a situation is facilitated by auto-hyponymy and auto-troponymy @xcite , which fall within the definition of vertical polysemy @xcite . auto-hyponymy and auto-troponymy in semantic hierarchies of wordnet have already been studied mainly as a criterion for grouping meanings of words @xcite , but also for reducing polysemy (i.e. reducing the number of terms for their coarser distinction) @xcite . in this paper, however, we are going to look at the possible substructures of semantic hierarchies that can only be formed by vertical polysemy. we discovered that polysemy structures caused by vertical polysemy help us identify both the previously handled basic polysemy structures, such as chain and triangle @xcite , but also those that have not previously been associated with vertical polysemy. by studying such polysemy structures, we also were led to cycles and structures containing up to 20 vertical polysemy cases, which we judge are likely to be errors. the paper is structured as follows: section 2 gives the theoretical background to understand the main body of the article. next, section 3 is dedicates to the overview of polysemy structures from the perspective of previous work. section 4 describes the algorithm to detect specific polysemy structures from wordnet semantic hierarchies. section 5 focuses on the case study of estonian wordnet. section 6 gives an overview of the 11 wordnets uploaded to the omw environment. section 7 concludes the paper and presents future work. ## theoretical background this section aims to give some understanding of the theoretical basis of the discussed topic. here we define the concept of polysemy and provide an overview of different polysemy structures. ## previous work: overview of polysemy structures previous work in relation to auto-hyponymy (also auto-troponymy) involves finding sense clusters of polysemous words @xcite and reducing polysemy structures in wordnet semantic hierarchies to transform its term (word) senses from fine-grained to coarse-grained ones @xcite . the nearest work for our approach is (jen-yi, yang, tseng, & chu-ren, 2002). the authors' broader goal was to create a bilingual network for chinese and english, exploring the hierarchies of verbs, since there is approximately twice as much polysemy among the verbs as among the nouns. they aimed to find semantic patterns, hoping that these are helpful in multilingual information retrieval task. in their work, they distinguish five types of patterns calling them specifically the 3 http://wordnetweb.princeton.edu/perl/webwn sense clusters of polysemous verbs or polysemic patterns. very generally, these patterns take into account cases where two or more synonym sets contain the same term in their sets and are tightly related to each other in the semantic structure. the names of these patterns are sisters, twins, child, chain and triangle. next, we describe each one of them shortly (jen-yi, yang, tseng, & chu-ren, 2002). ## description of the algorithm in our study, we find both the structures of polysemy and the statistics that describe these structures in one or another aspect. these statisticians are general enough not to pay attention to them in terms of the algorithm description. thus, here we describe the only algorithm that finds all polysemy structures caused by vertical polysemy. ## case study of estonian wordnet in this section, we describe one word and its senses from the estonian wordnet as an example of a vertical polysemy structure where it was possible to revise senses and reduce too fine-grained separation of senses. ## polysemy structures in wordnets in this section, we strive to capture a broader picture of the state of the wordnets in terms of vertical polysemy affected by polysemic structures. for that reason, we highlight the most specific structures caused by vertical polysemy. in addition, we provide tables for wordnets that characterize the structures of polysemy and describe the specificities that arise. wordnets we are using here are shown in ## conclusion the study of polysemy in wordnet semantic hierarchies is essential because it is one of the central problems that needs to be considered in the case of distinctive nlp tasks that require semantic analysis. for this reason, we aimed to capture what polysemic structures occur in the wordnets uploaded to omw. in more detail, we studied the estonian wordnet, where polysemy has been kept under the spotlight for years. that is also the reason why its results were not as extreme as any other wordnets. however, we did find a couple of examples here, yet only one that needed correction. thus in estonian wordnet polysemy structures of auto-hyponyms do not represent major problems of finegrained senses, only few cases are present. many of the structures of polysemy are caused by the economy principles of languages, i.e. general meaning is transferred to a more specific meaning or to a domain terminology. some auto-hyponymy cases can be solved, if we introduced new semantic relations to estonian wordnet, for example the domain-relation. by studying eleven wordnets, we discovered some unexpected polysemic structures. these are structures that by their nature are not new, but are not previously presented as closed chunks caused by vertical polysemy (as substructures in the semantic hierarchy). these polysemic structures are:  multiple inheritance  shortcut structure  the longest chain (path) these structures are unexpectedly frequent in many of the wordnets. the longest chain found had five vertices, longer than the four that have been previously discussed. the study of vertical polysemy relations in the 11 different wordnet networks reveals the impact of the individual choices, as it is a choice of the lexicographer, how to organize the polysemic senses in the wordnet hierarchy (e.g. as a configuration of a sister structure or as two children instead). this is the main reason behind the size of polysemic clusters in particular hierarchies. the code to discover and visualize these structures will be incorporated into the open multilingual wordnet, which can be accessed online or run on your own machine.