Linking SIL Semantic Domains to W ordnet and Expanding the A bui W ordnet through Rapid Word Collection Methodology (2023)

Abstract: In this paper we describe a new methodology to expand the Abui Wordnet through data collected using the Rapid Word Collection (RWC) method – based on SIL’s Semantic Domains. Using a multilingual sense-intersection algorithm, we created a ranked list of concept suggestions for each domain, and then used the ranked list as a filter to link the Abui RWC data to wordnet. This used translations from both SIL’s Semantic Domain’s structure and example words, both available through SIL’s Fieldworks software and the RWC project. We release both the new mapping of the SIL Semantic Domains to wordnet and an expansion of the Abui Wordnet.

## introduction in this paper we describe the second phase of the abui wordnet construction which merges the data collected through the rapid word collection method (rwc), as described in section 2.2, into the abui wordnet v1.0 (see section 1.1). the rwc method is built around the sil semantic domains ontology, discussed in detail in section 2.1. much of the work discussed in this paper is related to the necessity of providing structure to data collected using common methods in field linguistics. the sil semantic domains, and the rapid word collection methodology in particular, support lexicographic work on endangered languages and significantly accelerate dictionary production. this paper looks into solving these issues by providing support to link unstructured types of data collected on the field to the abui wordnet. ## 2 data collection in this section we provide an introduction to the structure and method for collecting our abui data. ## methodology the work presented in this paper uses and extends the idea of multilingual sense intersection @xcite . the methodology is illustrated in figure 4 : it attempts to perform word sense disambiguation (wsd)i.e., to determine the most likely sense of a word with reference, e.g., to a wordnet hierarchy -by restricting the available semantic space through the intersection of semantic spaces of aligned translations of that same word. this method has been used to create new wordnets, such as the coptic wordnet @xcite and, most recently, also to kick-start the development of the abui wordnet from field data (kratochvíl and morgado da costa, 2022). in this work, we employ this same concept in two ways: i) we use multilingual sense intersection to perform wsd to map the sil semdoms data to the open multilingual wordnet (omw, @xcite ; ii) we use the results of the previous step as a pivot to map abui data collected through rwc workshops to the abui wordnet. ## results and evaluation in this section we discuss three different things: i) the results of mapping the semdoms to the omw using the data extracted from sil fieldworks; ii) the results of producing sense candidates for the abui wordnet through multilingual sense intersection using the rwc method with and without using i) as as filtering step; and iii) the results of hand-checking sense candidates produced in ii) by a group of linguists and native speakers. ## release notes this paper releases two new sets of data: i) the mapping of sil semantic domains to omw (through pwn 3.0 offsets); and ii) a new extension to the abui wordnet. the mapping of sil semantic domains to omw will be shared under a creative commons attribution-sharealike 4.0 license (following the original license for this resource). in the future, we will attempt to liaise with sil and open the license further. this data will be released as two tsv files, one for the semdom identifier titles, and another ## conclusion in this paper we have used the idea of multilingual sense intersection for two ends: i) to create a new language resource -a mapping of sil semantic domains to the structure of the open multilingual wordnet; and ii) to use this new semantic resource as a filter to expand the abui wordnet with data collected using the rapid word collection method (which relies on the sil semantic domains). we have yielded very positive results for both goals. we have linked more than 47,500 omw concepts to the sil semantic domains (with a high confidence score), and we have generated more than 10,500 new sense candidates for the abui wordnet. human evaluation has offered a confidence score for these sense candidates between 87.6% and 99.6%. we hope our work inspires other linguists with data linked to sil semantic domains to follow in our footsteps and to link their data to structures such as the omw. we hope that lexicographic work on low-resource languages may benefit from both the omw structure and the sil experience in rapid lexicographic work involving language communities.