A Taxonomic Classification of W ord N et Polysemy Types (2016)

Abstract: WordNet represents polysemous terms by capturing the different meanings of these terms at the lexical level, but without giving emphasis on the polysemy types such terms belong to. The state of the art polysemy approaches identify several polysemy types in WordNet but they do not explain how to classify and organize them. In this paper, we present a novel approach for classifying the polysemy types which exploits taxonomic principles which in turn, allow us to discover a set of polysemy structural patterns.

## introduction polysemy in wordnet @xcite corresponds to various kinds of linguistic phenomena and can be grouped into various polysemy types @xcite . although wordnet was inspired by psycholinguistic and semantic principles @xcite , its conceptual dictionary puts greater emphasis on the lexical level rather than on the semantic one @xcite . lexicalizing polysemous terms without any further information about their polysemy type affects the usability of wordnet as a knowledge resource for semantic applications @xcite . in general, the state of the art approaches suggests different solutions to the polysemy problem. the most prosperous among these approaches are the regular/systematic polysemy approaches such as @xcite ) @xcite . these approaches propose the semantic regularity as a basis for classification of the polysemy classes and offer different solutions that commensurate the nature of the discovered polysemy types. despite the diversity and depth of the state of the art solutions, no or very little attention has been given, so far, to the principles or rules used to identify polysemy types. in fact, none of these approaches can explain how to identify the polysemy types of the discovered polysemy structural patterns or how to differentiate for example, between homonymy and metaphoric structural patterns. although apersejan's semantic similarity criterion @xcite can be used to account for regularity in polysemy, it can not predict the polysemy type of the regular polysemy types in wordnet. our hypotheses in this paper is that identifying and differentiating between the polysemy types of the regular polysemy structural patterns requires understanding the hierarchical structure of wordnet and, thus, the criteria related to the taxonomic principles that the hierarchical structure of wordnet comply with or violates. in this paper, we show how to use two taxonomic principles as criteria for identifying the polysemy types in wordnet. based on these principles, we introduce a semi automatic method for discovering and identifying three polysemy types in wordnet. the paper is organized as follows. in section two, we discuss the problem. in section three, we introduce the formal definitions we use. in section four, we discuss the taxonomic principles that we use to discover three of the polysemy types in wordnet. in section five, we give an overview of our approach. in section six, we show how to use the taxonomic principles to identify metaphoric structural patterns. in section seven, we demonstrate how to determine specialization polysemy structural patterns. in section eight, we describe how to discover homonymy structural patterns. in section nine, we explain how to handle false positives in the structural patterns. in section ten, we present the results of our approach. in section eleven, we conclude the paper and depict our future work. wordnet is a machine readable online lexical database for the english language. based on psycholinguistic principles, wordnet has been developing since 1985, by linguists and psycholinguists as a conceptual dictionary rather than an alphabetic one @xcite . since that time, several versions of wordnet have been developed. in this paper, we are concerned with wordnet 2.1. wordnet 2.1. contains 147,257 words, 117,597 synsets and 207,019 word-sense pairs. the number of polysemous words in wordnet is 27,006, where 15776 are nouns. in this paper, we deal with polysemous nouns at the concept level only. we do not consider polysemy at the instance level. after removing the polysemous nouns that refer to proper names, the remaining polysemous nouns are 14530 nouns. wordnet does not differentiate between the types of the polysemous terms and it does not contain any information in terms of polysemy relations that can be conducted to determine the polysemy type between the synsets of a polysemous term. the researchers who attached the polysemy problem in wordnet gave different descriptions for the polysemy types in wordnet. for example, polysemy reduction approaches @xcite @xcite differentiate between contrastive polysemy and complementary polysemy. regular polysemy approaches such as (barque and chaumartin, 2009) @xcite @xcite ) @xcite give more refined classification of the polysemy types into metonymy, metaphoric, specialization polysemy, and homonymy. in one of our recent papers, compound noun polysemy is introduced as a new polysemy type beside the former four polysemy types in wordnet @xcite . so far, no polysemy reduction approaches have introduced a mechanism for classifying the polysemy types into contrastive and complementary. instead, these approaches adopt semantic and probabilistic rules to discover redundant and/or very fine grained senses. on the other hand, the regular polysemy approaches embrace a clear definition for classifying polysemous terms into regular and non regular polysemy @xcite . although, the definition of regular polysemy in these approaches is useful to distinguish between regular and non regular polysemy, these approaches do not reveal the principles or the criteria used to classify polysemous terms into polysemy types. in this paper, we explain how to use the exclusiveness property and the collectively exhaustiveness property @xcite for identifying the following polysemy types. 1 metaphoric polysemy: refers to the polysemy instances in which a term has literal and figurative meanings @xcite ). in the following example, the first meaning of the term fox is the literal meaning and the second meaning is the figurative. #1 fox: alert carnivorous mammal. #2 dodger, fox, slyboots: a shifty deceptive person. ## approach notations we begin with the basic notations. lemma is the basic lexical unit in wordnet that refers to the base form of a word or a collocation. based on this definition, we define a natural language term or simply a term as a lemma that belongs to a grammatical category; i.e., noun, verb, adjective or adverb. ## approach overview we exclude the structural patterns whose pattern root resides in the first and second level in word-net hierarchy. accordingly, any structural pattern whose root belongs to the synsets {entity, abstract entity, abstraction, physical entity, physical object } was automatically excluded. our hypothesis is that the pattern hyponyms in these structural patterns in general fulfill the exclusiveness and the exhaustiveness property. these patterns are subject to our current research in discovering metonymy structural patterns. on the other hand, exclusiveness and exhaustiveness property are not guaranteed for all structural patterns whose roots reside in the third level and beyond. the input of the algorithm is the taxonomic structure of wordnet, starting from level 3, after removing lexical redundancy in compound nouns @xcite . the output consists of three lists that contain specialization polysemy, metaphoric polysemy and homonymy instances. the first step of our algorithm is automatic, while the other two are manual. homographs patterns: this list contains the patterns whose corresponding instances are homonymy candidates. singleton patterns: the patterns in this group are those patterns that have one polysemy in-stance only and thus cannot be considered to be regular. ## metaphoric structural patterns identifying metaphoric patterns is based on the distinction between the literal meaning and the figurative meaning. our idea is that it is not possible for a literal and the figurative meaning to be collectively exhaustive. violating the exhaustiveness property in a structural pattern xr, p 1 , p 2 y may be a result of the following: in the following, we define metaphoric patterns structural pattern as follows. ## specialization polysemy structural patterns we use the exclusiveness property and the pattern root in a structural pattern to discover specialization polysemy candidates indirectly. the relation between the synsets in specialization polysemy is hierarchical. the hierarchical relation between the synsets in a specialization polysemy instance indicates that the exclusiveness property does not hold between synsets and thus between the structural pattern hyponyms. we define specialization polysemy patterns as follows. ## homonymy structural patterns we define homonymy patterns as follows. ## false positives identification in this section, we describe the third step of our approach. our task here is to process the four lists returned at the end of the pattern classification and remove false positives. these lists are the metaphoric polysemy list, the specialization polysemy list, the homonymy list, and a list of non regular (singleton patterns) list. this task can only be performed manually due to the implicit and missing information in synset glosses. our procedure for determining the polysemy class of a polysemy instance is based on the three definitions in the previous section, where we process the polysemy instances instance by instance to determine the the relation between the synsets of the polysemy instances. if a polysemy instance does not belong to the polysemy type it was assigned to (false positive instance), we assign it to its corresponding polysemy type. in the following, we give examples for false positives. the common parent structural pattern which was automatically assigned to the specialization polysemy type (step 1 in section 5) contains 180 false positive polysemy instances, 98 of them were identified as homonymy instances. one example is: #1 cardholder: a person who holds a credit card or debit card. metaphoric false positives (82 instances) were also identified in the common parent class. consider for example the following instance. #1 game plan: (figurative) a carefully thought out strategy for achieving an objective in war. ## results and evaluation the number of polysemy instances computed by the polysemy instances discovery algorithm is 41306. we excluded 28318 instances because the pattern roots of these instances reside in the first and the second level of the hierarchy as per the approach discussed in section 5.the remaining number of polysemy instances is 12988. these instances are divided in two groups as follow. 12988 of these instances belong to 1028 regular type compatible patterns and 1569 instances belong to single tone patterns. the classification of the pasterns and the result of the false positive removing is shown in the following tables. ## conclusion and future work in this paper, we have presented how to use two taxonomic principles for classifying the polysemy types in wordnet. we have demonstrated the usefulness of our approach on classifying three polysemy types, namely, specialization, metaphoric and homonymy. in this approach, we were able to discover all specialization polysemy structural patterns and subsets of the metaphoric and metonymy structural patterns. we aim to continue our work to study the metonymy patterns in the upper level of wordnet hierarchy, where we generalize our structural pattern definition as follows. definition 16 (generalized structural pattern). a structural pattern of polysemy instance @xmath0, s 1 , s 2 s is a triple p xr, p 1 , p 2 y, where a) r is the least common subsumer of s 1 and s 2 ; b) r ¦ p 1 and r ¦ p 2 ; c) p 1 ¦ s 1 and p 2 ¦ s 2 . our hypothesis is that in case of metonymy structural patterns: the nodes p 1 and p 2 fulfill the exclusiveness and the exhaustiveness properties and there is a part of relation between p 1 and p 2 . the conditions for metaphoric and homonymy structural patterns obtained by adapting the new structural definition remain the same as explained in this paper.