An Experiment: Using G oogle T ranslate and Semantic Mirrors to Create Synsets with Many Lexical Units (2018)

Abstract: One of the fundamental building blocks of a wordnet is synonym sets or synsets, which group together similar word meanings or synonyms. These synsets can consist either one or more synonyms. This paper describes an automatic method for composing synsets with multiple synonyms by using Google Translate and Semantic Mirrors’ method. Also, we will give an overview of the results and discuss the advantages of the proposed method from wordnet’s point of view.

## introduction three important aspects need to be considered while composing a wordnet @xcite : what type of a lexical resource to use, which building model @xcite to implement and what is the level of automation. wordnets can be built manually, semi-automatically, automatically and can be based on different bilingual or monolingual resources or corpora. this means that synsets can also be created either manually or (semi)automatically and wordnet builders have to decide if a synset contains one or many synonyms; the latter mentioned is a quite difficult task. finding and determining synonyms can often be complicated, for example in estonian wordnet there are two different synsets: 'hypogastrium' and 'abdomen' which belong to one synset @xcite . synonyms can be identified from monolingual explanatory dictionaries @xcite and bilingual dictionaries, text corpora, lexico-syntactic patterns and neural networks @xcite ; from wikipedia, spectral clustering and from multi-layered neural networks @xcite . also from parallel corpora @xcite and from using translations of other wordnet's synsets @xcite . this paper fills the gap of identifying multimember synsets by using google translate. despite that google translate has around 70 different languages in its system, in this experiment we only deal with estonian and english languages. however, throughout all experiment we exploit three linguistic data resources:  all unique lexical units from the synsets in princeton wordnet foot_0 (version 3.1) (pwn) @xcite )  all unique lexical units from the synsets of estonian wordnet foot_1 (estwn) (version 72) @xcite )  google translate foot_2 translations and source languages synsets connected with translations (see figure 1 ). ## previous work semantic mirroring method was initially introduced by norwegian researcher helge dyvik @xcite . among other things, he used semantic mirrors' method for automatic creation of norwegian wordnet. this method helped him to discover both synonym sets and semantic relations (mostly hyperonymy) successfully from parallel corpora. to the best of our knowledge, there haven't been any attempts to discover synsets by using google translate. however, google translate is being used as a "dictionary" to translate pwn glosses to in macedonian wordnet @xcite or to translate multiword expressions from pwn to arabic @xcite . ## method description in this section, we formalize the method of synonym sets' pairs for source and target languages mathematically as well as we explain this formalization through an example. the method described here follows the idea of the semantic mirrors' method. ## overview of the experiment google translate categorizes translations and synonym sets for source language's words: translations are distinguishable by the length of the bar underneath word noun (see figure 1 ). the longest bar indicates to a common translation (two times in this case), middle length indicates to uncommon translation (one time in this case), and the shortest bar presents the rare translations (five times in this case). based on the outputs of the queries, our experiment is divided into two approaches. the first approach counts only common categories, the second approach deals with all categories of the output. ## results of the experiment one of the general results is the synset to synset translations, which can be exploited to check and compare the translation equivalents in wordnets. estwn is composed manually and often the translation from estonian to english is complicated to find, here are the synonyms produced to english useful. ## discussion and conclusion for google translate unique lexical units from synsets of estwn and pwn were given as an input, because wordnets (at least estwn and pwn) represent among other words the core vocabulary of languages, which can be sensibly used exactly in this experiment. the second reason to use namely wordnets as an input to google translate is that the data is adequately comparable since they represent the same vocabulary. as a result, we received a lot of synsets with many lexical units (or synonyms). we considered these synsets to be correct and suitable, where at least two members are also synset members in a wordnet. our experiment showed that the majority of the synsets do not fill this requirementthey consist new words, or they are completely different from the synsets in wordnet. for example, there are synsets containing words from different part-ofspeeches or synsets combining different senses. many synsets include possible hyperonym (and hyponyms), for example, estonian 'komm, komvek, maistus' (candy, sweets), where 'maiustus' (sweets) acts more as a hyperonym for 'komm' (candy). on the other hand, it is possible to complement synsets already present in estwn with the synset members identified by the current method. our method identifies a significant amount of new words, which can be included into estwn and to the pwn. here it should be noted that from the new words 50% are nouns, 20% verbs, and 20% adjectives. if we compare these percentages with the estonian input words, which are accordingly 80%, 8% and 6% (the rest are mainly adverbs), then we can assume that google translate was able to produce significantly more new words for verbs and adjectives than for nouns