Liu Lei, Gong Tongxi, Shi Jianjun, Guo Yi
English Department, School of International Studies, Zhengzhou University, Zhengzhou, China.
Institute of Linguistics, Shanghai International Studies University, Shanghai, China.
Front Psychol. 2024 Aug 9;15:1430060. doi: 10.3389/fpsyg.2024.1430060. eCollection 2024.
A number of high-frequency word lists have been created to help foreign language learners master English vocabulary. These word lists, despite their widespread use, did not take word meaning into consideration. Foreign language learners are unclear on which meanings they should focus on first. To address this issue, 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. 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.
已经创建了许多高频词汇表来帮助外语学习者掌握英语词汇。这些词汇表尽管被广泛使用，但并未考虑词义。外语学习者不清楚他们应该首先关注哪些词义。为了解决这个问题，我们使用BERT模型对当代美国英语语料库（COCA）和英国国家语料库（BNC）进行了高精度的语义标注。从这些标注语料库中，我们计算了不同词义的语义频率，并筛选出5000个词义，创建了一个高频词义列表。随后，我们检查了该列表的有效性，并将其与已有的有影响力的词汇表进行了比较。该列表具有三个显著特点。第一，它在不同语料库中实现了稳定的覆盖范围。第二，它能更准确地识别高频词汇。它与GSL、NGSL和New-GSL等列表的覆盖范围相当，但词汇数量要少得多。特别是，它包含了一些曾经从高频列表中消失的日常词汇，且无需人工调整。第三，它清楚地描述了哪些词义最常用，因此初学者应该重点关注。这项研究代表了在大型语料库语义标注和基于语义频率创建词汇表方面的开创性努力。
