Semantic Entanglement on Verb Negation

Yuto Kikuchi, Kazuo Hara, Ikumi Suzuki

2021

Abstract

The word2vec, developed by Mikolov et al. in 2013, is an epoch-creating method that embeds words into a vector space to capture their fine-grained meaning. However, the reliability of word2vec is inconsistent. To evaluate the reliability of word vectors, we perform Mikolov’s word analogy task, where word୅, word୆, and wordେ are provided. Under the condition that word୆ exhibits a particular relation with word୅, the task involves searching the vocabulary and returning the most relevant word for wordେ for the same relation. We conduct an experiment to return negative words for verbs using word2vec for 100 typical Japanese verbs and investigate the effect of context (i.e., surrounding words) on correct or incorrect responses. It is shown that the task fails when the sense of verbs and negative relation are entangled because the semantic calculation of verb negation does not hold.

Paper Citation

in Harvard Style

Kikuchi Y., Hara K. and Suzuki I. (2021). Semantic Entanglement on Verb Negation. In Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-521-0, pages 71-78. DOI: 10.5220/0010560000710078

in Bibtex Style

@conference{data21,
author={Yuto Kikuchi and Kazuo Hara and Ikumi Suzuki},
title={Semantic Entanglement on Verb Negation},
booktitle={Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2021},
pages={71-78},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010560000710078},
isbn={978-989-758-521-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Semantic Entanglement on Verb Negation
SN - 978-989-758-521-0
AU - Kikuchi Y.
AU - Hara K.
AU - Suzuki I.
PY - 2021
SP - 71
EP - 78
DO - 10.5220/0010560000710078