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ORIGINAL RESEARCH article

Front. Psychol.
Sec. Psychology of Language
Volume 15 - 2024 | doi: 10.3389/fpsyg.2024.1430060
This article is part of the Research Topic Discourse, Conversation and Argumentation: Theoretical Perspectives and Innovative Empirical Studies, Volume III View all 10 articles

A High-frequency Sense List

Provisionally accepted
Tongxi Gong Tongxi Gong 1Lei Liu Lei Liu 2*Jianjun Shi Jianjun Shi 1Yi Guo Yi Guo 3
  • 1 Shanghai International Studies University, Shanghai, Shanghai Municipality, China
  • 2 Zhengzhou University, Zhengzhou, Henan Province, China
  • 3 Shanghai University of International Business and Economics, Shanghai, Shanghai Municipality, China

The final, formatted version of the article will be published soon.

    We semantically annotated the Corpus of Contemporary American English (COCA) and the British National Corpus (BNC) with high accuracy using a BERT model. From these annotated corpora, we calculated the semantic frequency of different senses and filtered out 5000 senses to create a High-frequency Sense List. Subsequently, we checked the validity of this list and compared it with established influential word lists. This list exhibits three notable characteristics. First, It achieves stable coverage in different corpora such as COCA and BNC. Second, it identifies high-frequency items with greater accuracy. It achieves comparable coverage with lists like GSL, NGSL, and New-GSL but with significantly fewer items.Especially, it includes everyday words that used to fall off high-frequency lists without requiring manual adjustments. Third, it describes clearly which senses are most frequently used and therefore should be focused on by beginning learners. This study represents a pioneering effort in semantic annotation of large corpora and the creation of a word list based on semantic frequency.

    Keywords: BERT, semantic annotation, Sense frequency, Word list, Large Language Model

    Received: 09 May 2024; Accepted: 22 Jul 2024.

    Copyright: © 2024 Gong, Liu, Shi and Guo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Lei Liu, Zhengzhou University, Zhengzhou, 450001, Henan Province, China

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