hrvatski jezikClear Cookie - decide language by browser settings

IRB-NLP at SemEval-2022 Task 1: Exploring the Relationship Between Words and Their Semantic Representations

Korenčić, Damir; Grubišić, Ivan (2022) IRB-NLP at SemEval-2022 Task 1: Exploring the Relationship Between Words and Their Semantic Representations. In: Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). Seattle, United States, Association for Computational Linguistics, pp. 36-59 .

[img] PDF - Published Version - article
Download (17MB)


What is the relation between a word and its description, or a word and its embedding? Both descriptions and embeddings are semantic representations of words. But, what information from the original word remains in these representations? Or more importantly, which information about a word do these two representations share? Definition Modeling and Reverse Dictionary are two opposite learning tasks that address these questions. The goal of the Definition Modeling task is to investigate the power of information laying inside a word embedding to express the meaning of the word in a humanly understandable way -- as a dictionary definition. Conversely, the Reverse Dictionary task explores the ability to predict word embeddings directly from its definition. In this paper, by tackling these two tasks, we are exploring the relationship between words and their semantic representations. We present our findings based on the descriptive, exploratory, and predictive data analysis conducted on the CODWOE dataset. We give a detailed overview of the systems that we designed for Definition Modeling and Reverse Dictionary tasks, and that achieved top scores on SemEval-2022 CODWOE challenge in several subtasks. We hope that our experimental results concerning the predictive models and the data analyses we provide will prove useful in future explorations of word representations and their relationships.

Item Type: Conference or workshop item published in conference proceedings (UNSPECIFIED)
Uncontrolled Keywords: deep learning ; natural language processing ; semantic representations ; codwoe ; definition modeling ; reverse dictionary
Subjects: NATURAL SCIENCES > Physics
Divisions: Division of Electronics
Depositing User: Ivan Grubišić
Date Deposited: 06 Feb 2024 15:46
DOI: 10.18653/v1/2022.semeval-1.5

Actions (login required)

View Item View Item


Downloads per month over past year

Increase Font
Decrease Font
Dyslexic Font