The University of Pittsburgh English Language Institute Corpus (PELIC)

IF 1.1 0 LANGUAGE & LINGUISTICS International Journal of Learner Corpus Research Pub Date : 2022-03-08 DOI:10.1075/ijlcr.21002.nai
Ben Naismith, Na-Rae Han, Alan Juffs
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引用次数: 2

Abstract

This report introduces the University of Pittsburgh English Language Institute Corpus (PELIC; Juffs et al., 2020), a publicly available 4.2-million-word learner corpus of written texts. Collected over seven years in the University of Pittsburgh’s Intensive English Program, these texts were produced by more than 1,100 students with diverse linguistic backgrounds and proficiency levels. Unlike most learner corpora which are cross-sectional, PELIC is longitudinal, offering greater opportunities for tracking development in a natural classroom setting. This potential is illustrated in an overview of the research conducted to date with these data. The report also provides a description of PELIC’s creation and contents, including how the texts have been managed to facilitate natural language processing. Overall, the corpus contributes to the field of learner corpus research by adding to the pool of freely and publicly available learner corpora, supplemented by a useful set of Python tools and tutorials for accessing these data.
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匹兹堡大学英语语言学院语料库
本报告介绍了匹兹堡大学英语语言学院语料库(PELIC;Juffs等人,2020),一个公开的420万字的书面文本学习者语料库。这些文本在匹兹堡大学的强化英语课程中收集了七年多的时间,由1100多名具有不同语言背景和熟练程度的学生编写。与大多数学习者语料库是横断面的不同,PELIC是纵向的,为在自然课堂环境中跟踪发展提供了更多的机会。这种潜力在对迄今为止利用这些数据进行的研究的概述中得到了说明。该报告还描述了PELIC的创建和内容,包括如何管理文本以促进自然语言处理。总的来说,该语料库通过增加免费和公开可用的学习语料库,并辅以一套有用的Python工具和访问这些数据的教程,为学习语料库研究领域做出了贡献。
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CiteScore
3.40
自引率
27.30%
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0
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Comparing theory-based models of grammatical complexity in student writing Review of Leńko-Szymańska & Götz (2022): Complexity, Accuracy and Fluency in Learner Corpus Research Review of Granger (2021): Perspectives on the L2 Phrasicon: The view from learner corpora The effect of linguistic and extralinguistic features on EFL adverb placement On learner characteristics and why we should model them as latent variables
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