Personalized P age R ank with Syntagmatic Information for Multilingual Word Sense Disambiguation (2020)

Abstract: Exploiting syntagmatic information is an encouraging research focus to be pursued in an effort to close the gap between knowledge-based and supervised Word Sense Disambiguation (WSD) performance. We follow this direction in our next-generation knowledge-based WSD system, SyntagRank, which we make available via a Web interface and a RESTful API. SyntagRank leverages the disambiguated pairs of co-occurring words included in SyntagNet, a lexical-semantic combination resource, to perform state-of-the-art knowledge-based WSD in a multilingual setting. Our service provides both a user-friendly interface, available at http://syntagnet.org/ , and a RESTful endpoint to query the system programmatically (accessible at http://api.syntagnet.org/ ).

## introduction in natural language processing, word sense disambiguation (wsd) is an open problem concerning lexical ambiguity. it is aimed at determining which sense -among a finite inventory of many -is evoked by a given word in context @xcite . this challenge has been tackled by exploiting huge amounts of hand-annotated data in a supervised fashion @xcite @xcite or, alternatively, by harnessing structured information @xcite @xcite , such as that available within existing lexical knowledge bases (lkbs) like wordnet @xcite . despite achieving better overall results, supervised systems require tremendous efforts in order to produce data for several languages @xcite , whereas knowledge-based approaches can easily be applied in multilingual environments due to the wide array of languages covered by lkbs like ba-belnet foot_0 @xcite , or the open multilingual wordnet @xcite . moreover, it is widely acknowledged that the performance of a knowledge-based wsd system is strongly correlated with the structure of the lkb employed @xcite @xcite . in fact, the knowledge available within lkbs reflects the fact that words can be linked via two types of semantic relations: paradigmatic relations -i.e. the most frequently encountered relations in lkbs -concern the substitution of lexical units, and determine to which level in a hierarchy a language unit belongs by semantic analogy with units similar to it; conversely, syntagmatic relations concern the positioning of such units, by linking elements belonging to the same hierarchical level (e.g., words), which appear in the same context (e.g., a sentence). as a case in point, a paradigmatic relation exists, independently of a given context, between the words farm n and workplace n (where a farm is a type of workplace), whereas a syntagmatic relation is entertained between the words work v and farm n , e.g., in the sentence 'her husband works in a farm as a labourer.' in our most recent study @xcite , syn-tagnet), we provided further evidence that the nature of lkbs impacts on system performance: the injection of syntagmatic relations -in the form of disambiguated pairs of co-occurring wordsinto an existing lkb biased towards paradigmatic knowledge enables knowledge-based systems to rival their supervised counterparts. to make the above results accessible to the research community, in this paper we introduce a web interface and a restful api for syntagrank, our multilingual wsd system, which applies the personalized pagerank (ppr) algorithm @xcite to an lkb made up of wordnet, the princeton wordnet gloss corpus (pwng) and the lexical-semantic syntagmatic combinations available in the syntagnet resource. syntagrank is the first system to perform multilingual wsd by leveraging an underlying lkb connecting a sizeable amount of syntagmatically-related concepts. ## preliminaries our disambiguation algorithm relies on an lkb, i.e. a graph in which each node represents a concept, and each connection between nodes represents a semantic relation. in this section we describe the lkbs whose resulting union we use as our reference graph, and then go on to provide details of the ppr algorithm. ## architecture of syntagrank syntagrank is a knowledge-based disambiguation system which uses the ppr algorithm to determine the most appropriate sense of a given word in context. this approach, already discussed by @xcite , is here presented in an optimized, rebuilt version, employing the lkbs described in section 2.1 to achieve state-of-the-art knowledgebased performance across five languages: english, german, french, spanish, and italian. our architecture (figure 1 ) is composed of three main modules: (i) multilingual nlp pipeline, (ii) candidate retrieval, and (iii) disambiguator. ## web interface figure 2 shows the web interface of syntagrank. its components are explained below. a. query the system takes as input the text to be processed 8 . users can enter either single words, multiword expressions (mwes), or full sentences as input queries. in the event that the input text is a sentence, this will be processed by the disambiguator and the system will return a disambiguated sentence (see paragraph c). otherwise, if the query matches an entry in the syntagnet database, the interface will switch to the syntagnet explorer (see section 4.1) to display all the lexical-semantic combinations available for all the senses of the word/mwe provided as input query. ## evaluation in order to assess its performance, we tested syn-tagrank on the five english all-words wsd evaluation datasets standardized according to wordnet 3.0 in the framework of @xcite , namely: senseval-2 @xcite , senseval-3 @xcite , @xcite @xcite @xcite . as regards the appraisal of synta-grank in a multilingual setting, we used the german, spanish, french and italian annotations available in the amended version of the semeval-2013 and semeval-2015 evaluation datasets 10 , which is accordant with the babelnet api 4.0.1 graph and 10 made available at https://github.com/ sapienzanlp/mwsd-datasets . in ## conclusion in this paper we presented and described the architecture of syntagrank, our state-of-the-art knowledge-based system for multilingual word sense disambiguation using syntagmatic information. we also provided details concerning the use of syntagrank's web interface and restful api, accessible at http://syntagnet.org/ and http://api.syntagnet.org , respectively.