Initial Experiments for Building a G uarani W ord N et (2023)

Abstract: This paper presents a work in progress about creating a Guarani version of the WordNet database. Guarani is an indigenous South American language and is a low-resource language from the NLP perspective. Following the expand approach, we aim to find Guarani lemmas that correspond to the concepts defined in WordNet. We do this through three strategies that try to select the correct lemmas from Guarani-Spanish datasets. We ran them through three different bilingual dictionaries and had native speakers assess the results. This procedure found Guarani lemmas for about 6.5 thousand synsets, including 27% of the base WordNet concepts. However, more work on the quality of the selected words will be needed in order to create a final version of the dataset.

## introduction guarani is an indigenous south american language spoken by around 6.5 million native speakers, mainly in paraguay and in parts of bolivia, argentina and brazil. despite being one of the most widely spoken languages in the region, it has received little attention from a computational linguistic perspective. in the latest years, interest in natural language processing (nlp) research for indigenous languages of the americas has increased, and nowadays, a number of researchers are building tools and resources for many of these languages, such as multilingual corpora @xcite . however, the creation of lexical databases and ontologies, such as wordnets, is only very recently starting to gather attention. wordnet @xcite is a lexical database, originally created for english but later on for many other languages (e.g. @xcite , that organizes concepts in an ontology of inter-related terms. the basic unit of wordnet is the synset, defined as a set of words that could be used interchangeably, at least in some context, and is similar to the notion of a sense or meaning in a dictionary. synsets are organized in an ontology with hyponymy as the central relation between concepts, but also including (depending on the pos) other relations such as meronymy, antonymy or implication. the concepts stored in wordnet belong to one of the four lexical categories: nouns, verbs, adjectives and adverbs. historically there have been two main approaches to building wordnets @xcite , which are: manually creating a new set of concepts for each language and establishing links to the original princeton wordnet (named the merge approach), or using the original structure of princeton wordnet and translating the lemmas corresponding to the different concepts into the target language (named the expand approach). in this paper, we present a work in progress for building a wordnet database for the guarani language using the expand approach. we collected different bilingual datasets (i.e. guarani-spanish dictionaries), and implemented some heuristics to select the correct guarani lemmas that correspond to wordnet synsets. then native speakers annotated a sample of the results obtained by the heuristics in order to assess the quality of the built resource. ## related work there have been very few attempts at creating wordnets for indigenous american languages. two of them are about languages spoken mainly in peru, @xcite , and several varieties of quechua @xcite . previous attempts for quechua do not focus on building a wordnet ontology, but include using links to the spanish wordnet in order to help word sense disambiguation @xcite or morphological analysis @xcite . @xcite describe an attempt to build wordnets in several indigenous african languages. these attempts, as well as the ones mentioned above, generally use the expand approach to building wordnets, as it is the easiest one to use when at least there are bilingual datasets available. our work is, as far as we know, the first attempt to build a wordnet for guarani. we focus on the modern paraguayan variety of guarani. similarly to @xcite , we use the spanish version of wordnet to support the translation, because there are more guarani-spanish bilingual resources available. guarani is a low-resource language @xcite and, like other languages in this category, it lacks large monolingual and parallel corpora to build even some relatively simple nlp applications. there are some small multilingual @xcite and bilingual @xcite corpora that include guarani, and even the newest version of the google translate tool includes guarani as one of its options foot_0 , but so far, the size and performance of these resources is not enough to obtain accurate lexical information. ## guarani language modern paraguayan guarani belongs to the tupi-guarani family, part of a posited tupian stock comprising between 60 and 70 different languages. the tupi-guarani family is the largest family within the tupian stock, and within it, guarani is the language with the most speakers. tupian languages are spoken in brazil, argentina, bolivia, french guiana, paraguay and peru. ## process this section describes the heuristics we use to select guarani lemmas for the synsets, and the datasets we obtain the information from. ## results and evaluation the rules also found possible lemmas for 1,263 (around 27%) out of 4,689 synsets considered base concepts of wordnet 4 , defined to be high in the semantic hierarchy and to have many connections to other concepts. ## conclusions we presented a work in progress on building a version of the wordnet lexical database for guarani, an indigenous south american language. our process obtains data from three bilingual guarani-spanish dictionaries, and we implemented three simple selectors that decide which guarani lemmas should be used as the translation of the lemmas present in the spanish wordnet synsets. the selectors are monosemy, single translation and factorization. we extracted lemmas for 6,519 synsets, but the quality of the selected lemmas is highly variable. the factorization method is the one that has the highest precision according to the human annotators (around 76%), and the sources with the highest precisions are dc (71%) and wiktionary (68%). however, there is still a lot of room for improvement. as future work, we plan to expand the manual evaluation in order to have a bigger set of curated synsets and lemmas, design new selectors that could extract better information from the sources, and collect or create more datasets, for example, using the existing bilingual corpora or mt systems.