Using early LLMs for corpus linguistics: Examining ChatGPT's potential and limitations

研究成果: ジャーナルへの寄稿学術誌査読

抄録

This study evaluates the extent to which information can be obtained from early Large Language Models (LLMs) for corpus linguistic research. Various tasks were conducted using ChatGPT 3.5, such as generating word frequency lists, collocations, words that fit certain grammatical patterns, and identifying genres. The generations were then compared with the search results from a large-scale general corpus (COCA). While favorable results were not achieved in identifying the genres of words or paragraphs, there was notable congruence in the frequency lists (75.0 %), collocations (42.8 %), and grammatical patterns (53.0 %) for the top 20 items. Even when the generated items did not perfectly match those from COCA, it was evident that high-frequency items were produced. Although LLMs may not be sufficient for rigorous academic research, the results are adequate for discerning overall trends or assisting learners. In addition, the results of this study show that the ability to search at the phrase level is an advantage of using LLMs for corpus research.

本文言語英語
論文番号100089
ジャーナルApplied Corpus Linguistics
4
1
DOI
出版ステータス出版済み - 4月 2024

!!!All Science Journal Classification (ASJC) codes

  • 言語学および言語
  • 社会科学(その他)

フィンガープリント

「Using early LLMs for corpus linguistics: Examining ChatGPT's potential and limitations」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル