Some strategies for the improvement of a S panish W ord N et (2016)

Abstract: Although there are currently several versions of Princeton WordNet for different languages, the lack of development of some of these versions does not make it possible to use them in different Natural Language Processing applications. So is the case of the Spanish Wordnet contained in the Multilingual Central Repository (MCR), which we tried unsuccessfully to incorporate into an anaphora resolution application and also in search terms expansion. In this situation, different strategies to improve MCR Spanish WordNet coverage were put forward and tested, obtaining encouraging results. A specific process was conducted to increase the number of adverbs, and a few simple processes were applied which made it possible to increase, at a very low cost, the number of terms in the Spanish WordNet. Finally, a more complex method based on distributional semantics was proposed, using the relations between English Wordnet synsets, also returning positive results.

## introduction the multilingual central repository @xcite follows the model proposed by the eurowordnet project. eurowordnet @xcite is a multilingual lexical database with wordnets for several european languages, structured in the same way as princeton's wordnet. the mcr comprises five different languages: english, spanish, catalan, basque and galician. the inter-lingual-index (ili) allows us to link the words in one language with their equivalent translation in any of the other languages, thanks to the automatically generated mappings among wordnet versions. for example: the ili identifier "ili-30-02084071-n" corresponds both to the english synset "eng-30-02084071-n" with lemmas "dog, domestic dog", and to the spanish synset "spa-30-02084071-n" with lemmas "can, perro". in addition, it corresponds to the basque synset "eus-30-02084071-n" with lemmas "zakur, or, txakur", to the synset "cat-30-02084071-n" for catalan with lemmas "ca, canis familiaris", and also "glg-30-02084071-n" for galician with lemmas "can, canis familiaris". the current ili version corresponds to wordnet 3.0. all identifiers stem from the original synset in english. in the previous example there is a translation for each one of the languages, however, this is not the most common scenario. the mcr is incomplete, at least for the spanish version. this document presents several strategies to extend the coverage of the spanish version. an in-depth analysis of the different problems of the spanish mcr is presented in section 2, and section 3 describes several processes to enhance it. section 4 presents the evaluations carried out for the strategies proposed and section 5 presents final observations on the general results and the possibility to launch an enhanced version on line. ## strategies to improve wordnet to improve the existing spanish wordnet we conducted tests with processes that we have called "selectors", following the terminology already used in the field (wonef). a selector is a mechanism that, when applied to an english synset, will choose the translation or translations for the spanish synset based on the original in english. previously defined selectors were tested, supported by apertium and wiktionary translators, and in addition, two new selectors were defined, one based on morphology and the other based on the exploitation of semantic relations between synsets, with frequentist criteria used in distributional semantics. selectors are applied in two differentiated stages, which are separately evaluated. ## evaluation of results we show evaluations for the initial selectors, for the phase 2 process and a global evaluation of results within a lexical semantics effort. ## evaluation of the results on corin lexicon to evaluate the results obtained in both phases we implemented a task to measure the semantic coverage on a small corpus, in this case corin. for this task we obtained all the lemmas in the corpus, applied freeling to know the grammatical category, and then searched wordnet. this process was first executed with the original wordnet, our starting point, and then with the resulting wordnet. the aim was to measure the improvement in the coverage of the existing lemmas in the corpus under study of the resulting wordnet regarding the current wordnet. we must remember that the process to improve wordnet was executed on a random set of 1000 synsets per pos. the results obtained must be weighed considering the percentage these synsets represent within the total number of synsets for each pos. these percentages are shown in the following table.