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Found 21 papers, 3 papers with code
CILI: the Collaborative Interlingual Index
This paper introduces the motivation for and design of the Collaborative InterLingual Index (CILI).
Tuning Hierarchies in Princeton WordNet
Many new wordnets in the world are constantly created and most take the original Princeton WordNet (PWN) as their starting point.
An Analysis of WordNet’s Coverage of Gender Identity Using Twitter and The National Transgender Discrimination Survey
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.
Interdependencies of Gender and Race in Contextualized Word Embeddings
Recent years have seen a surge in research on the biases in word embeddings with respect to gender and, to a lesser extent, race.
A Corpus-based Syntactic Analysis of Two-termed Unlike Coordination
Coordination is a phenomenon of language that conjoins two or more terms or phrases using a coordinating conjunction.
English WordNet 2019 – An Open-Source WordNet for English
We describe the release of a new wordnet for English based on the Princeton WordNet, but now developed under an open-source model.
Building ASLNet, a Wordnet for American Sign Language
We discuss the creation of ASLNet by aligning the Princeton WordNet (PWN) with SignStudy, an online database of American Sign Language (ASL) signs.
Implementing ASLNet V1.0: Progress and Plans
We report on the development of ASLNet, a wordnet for American Sign Language (ASL).
Linking WordNet to 3D Shapes
We describe a project to link the Princeton WordNet to 3D representations of real objects and scenes.
Human and Automatic Interpretation of Romanian Noun Compounds
Determining the intended, context-dependent meanings of noun compounds like "shoe sale" and "fire sale" remains a challenge for NLP.
MABEL: Attenuating Gender Bias using Textual Entailment Data
To this end, we propose MABEL (a Method for Attenuating Gender Bias using Entailment Labels), an intermediate pre-training approach for mitigating gender bias in contextualized representations.
Mitigating Gender Bias in Machine Translation through Adversarial Learning
Machine translation and other NLP systems often contain significant biases regarding sensitive attributes, such as gender or race, that worsen system performance and perpetuate harmful stereotypes.
Extending and Improving Wordnet via Unsupervised Word Embeddings
Our methods require very few linguistic resources, thus being applicable for Wordnet construction in low-resources languages, and may further be applied to sense clustering and other Wordnet improvements.
Automated WordNet Construction Using Word Embeddings
To evaluate our method we construct two 600-word testsets for word-to-synset matching in French and Russian using native speakers and evaluate the performance of our method along with several other recent approaches.
Encoding Adjective Scales for Fine-grained Resources
We propose an automatic approach towards determining the relative location of adjectives on a common scale based on their strength.
Empirical Comparisons of MASC Word Sense Annotations
We analyze how different conceptions of lexical semantics affect sense annotations and how multiple sense inventories can be compared empirically, based on annotated text.
The MASC Word Sense Corpus
The MASC project has produced a multi-genre corpus with multiple layers of linguistic annotation, together with a sentence corpus containing WordNet 3. 1 sense tags for 1000 occurrences of each of 100 words produced by multiple annotators, accompanied by indepth inter-annotator agreement data.
