Verbs like make, have and get present challenges for applications requiring automatic word sense discrimination.These verbs are both highly frequent and polysemous, with semantically "full" readings, as in make dinner, and "light" readings, as in make a request.Lexical resources like WordNet encode dozens of senses, making discrimination difficult and inviting proposals for reducing the number of entries or grouping them into coarser-grained supersenses.We propose a data-driven, linguistically-based approach to establishing a motivated sense inventory, focusing on make to establish a proof of concept.

We report on the development of ASLNet, a wordnet for American Sign Language (ASL).ASLNet V1.0 is currently under construction by mapping easy-to-translate ASL lexical nouns to Princeton WordNet synsets.We describe our data model and mapping approach, which can be extended to any sign language.Analysis of the 390 synsets processed to date indicates the success of our procedure yet also highlights the need to supplement our mapping with the "merge" method.We outline our plans for upcoming work to remedy this, which include use of ASL free-association data.

We discuss the creation of ASLNet by aligning the Princeton WordNet (PWN) with SignStudy, an online database of American Sign Language (ASL) signs.This alignment will have many immediate benefits for first-and second-sign language learners as well as ASL researchers by highlighting semantic relations among signs.We begin to address the interesting theoretical question of to what extent the wordnet-style organization of the English lexicon (and those of wordnets in other spoken languages) is applicable to ASL, and whether ASL requires positing additional, language-or modality-specific relations among signs.Significantly, the mapping of SignStudy and PWN provides a bridge between ASL and the worldwide wordnet community, which comprises speakers of dozens of languages working in academic and language technology settings.

We describe the release of a new wordnet for English based on the Princeton WordNet, but now developed under an open-source model.In particular, this version of WordNet, which we call English WordNet 2019, which has been developed by multiple people around the world through GitHub, fixes many errors in previous wordnets for English.We give some details of the changes that have been made in this version and give some perspectives about likely future changes that will be made as this project continues to evolve.

We describe a project to link the Princeton WordNet to 3D representations of real objects and scenes.The goal is to establish a dataset that helps us to understand how people categorize everyday common objects via their parts, attributes, and context.This paper describes the annotation and data collection effort so far as well as ideas for future work.

This paper introduces the motivation for and design of the Collaborative InterLingual Index (CILI).It is designed to make possible coordination between multiple loosely coupled wordnet projects.The structure of the CILI is based on the Interlingual index first proposed in the Eu-roWordNet project with several pragmatic extensions: an explicit open license, definitions in English and links to wordnets in the Global Wordnet Grid.

While gender identities in the Western world are typically regarded as binary, our previous work (Hicks et al., 2015) shows that there is more lexical variety of gender identity and the way people identify their gender.There is also a growing need to lexically represent this variety of gender identities.In our previous work, we developed a set of tools and approaches for analyzing Twitter data as a basis for generating hypotheses on language used to identify gender and discuss genderrelated issues across geographic regions and population groups in the U.S.A.In this paper we analyze the coverage and relative frequency of the word forms in our Twitter analysis with respect to the National Transgender Discrimination Survey data set, one of the most comprehensive data sets on transgender, gender non-conforming, and gender variant people in the U.S.A.We then analyze the coverage of WordNet, a widely used lexical database, with respect to these identities and discuss some key considerations and next steps for adding gender identity words and their meanings to WordNet.

Many new wordnets in the world are constantly created and most take the original Princeton WordNet (PWN) as their starting point.This arguably central position imposes a responsibility on PWN to ensure that its structure is clean and consistent.To validate PWN hierarchical structures we propose the application of a system of test patterns.In this paper, we report on how to validate the PWN hierarchies using the system of test patterns.In sum, test patterns provide lexicographers with a very powerful tool, which we hope will be adopted by the global wordnet community.

In this paper, we introduce a methodology for mapping linguistic ontologies lexicalized across different languages.We present a classification-based semantics for mappings of lexicalized concepts across different languages.We propose an experiment for validating the proposed cross-language mapping semantics, and discuss its role in creating a gold standard that can be used in assessing cross-language matching systems.