Guangwai-Lancaster Chinese Learner Corpus
A brief description
Guangwai-Lancaster Chinese Learner Corpus (CLC), a 1.2-million-word corpus of learner Mandarin Chinese, which is a result of the collaboration between Guangdong University of Foreign Studies and Lancaster University, represents a new addition to corpora of L2 Chinese. The corpus has both a spoken (621,900 tokens, 48%) and a written (672,328 tokens, 52%) part and covers a variety of task types and topics. It is fully error tagged. It can be used to explore various theoretical and practical issues pertaining to the acquisition of Chinese as a foreign language.
Development team
Prof. Hai Xu (Guandong University of Foreign Studies)
Dr. Richard Xiao (Lancaster University)
Dr. Vaclav Brezina (Lancaster University)
Contact
Prof. Hai Xu: xuhai1101@gdufs.edu.cn
Dr. Vaclav Brezina: v.brezina@lancaster.ac.uk
The funding for the corpus was obtained by Dr. Richard Xiao to whom the corpus is also dedicated.
ACKNOWLEDGEMENT
The building of the corpus was supported by the British Academy IPM Scheme, Grant No. PM120462.
Tools to work with the Guangwai-Lancaster Chinese Learner Corpus
A complete set of Sketch Engine tools is available to work with this Chinese learner corpus to generate:
- word sketch – Chinese collocations categorized by grammatical relations
- thesaurus – synonyms and similar words for every word
- keywords – terminology extraction of one-word and multi-word units
- word lists – lists of Chinese nouns, verbs, adjectives etc. organized by frequency
- n-grams – frequency list of multi-word units
- concordance – examples in context
- text type analysis – statistics of metadata in the corpus
Changelog
English Web 2020 (enTenTen20)
version ententen20_tt31_1 (April 2022)
- 36.5 billion words
- TreeTagger pipeline version 3.1
- further cleaning and spam removing
- genre annotation and topic classification
version ententen20_tt31 (April 2021)
- 38 billion words (downloaded by SpiderLing in Nov & Dec 2019, Nov & Dec 2020 and Jan 2021)
- TreeTagger pipeline version 3.1
- samples from the biggest web domains were manually checked and content with poor linguistic quality was removed.
English Web 2018 (enTenTen18)
version enTenTen18_tt31 (February 2021)
- 21.9 billion words (Oct & Nov 2018; Jan, Nov & Dec 2017; Nov & Dec 2016; mainly from 2018)
- TreeTagger pipeline version 3.1
- manually checking of biggest web domains (account for 70% of all texts) and content with poor linguistic quality was removed.
English Web 2015 (enTenTen15)
- initial size 28 billion words
version 2 (spring 2017)
- 15 billion words
- TreeTagger pipeline version 2
version enTenTen15_tt31 (March 2020)
- 13 billion words
- TreeTagger pipeline version 3.1
- topic classification (according to dmoz.org)
- depth analysis of spam and its removal including too short documents
English Web 2013 (enTenTen13)
version ententen13_tt2 (2014)
- 19 billion words
- TreeTagger pipeline version 2
version ententen13_tt2_1 (fall 2016)
- new version of word sketch grammar
- dynamic attribute doc.website instead of doc.t2ld
English Web 2012 (enTenTen12)
version ententen12_sample40M (14 June 2012)
- sample of corpus – 3.7 billion words
- crawled by SpiderLing in May 2012
- encoded in UTF-8
version ententen12_1 (2012)
- full corpus – 11 billion words
English Web 2008 (enTenTen08)
version 1 (15 November 2010)
- initial version – 3.3 billion tokens
- crawled by Heritrix in 2008
- encoded in Latin1
Bibliography
TenTen corpora
SUCHOMEL, Vít. Better Web Corpora For Corpus Linguistics And NLP. 2020. Available also from: https://is.muni.cz/th/u4rmz/. Doctoral thesis. Masaryk University, Faculty of Informatics, Brno. Supervised by Pavel RYCHLÝ.
Jakubíček, M., Kilgarriff, A., Kovář, V., Rychlý, P., & Suchomel, V. (2013, July). The TenTen corpus family. In 7th International Corpus Linguistics Conference CL (pp. 125-127).
Suchomel, V., & Pomikálek, J. (2012). Efficient web crawling for large text corpora. In Proceedings of the seventh Web as Corpus Workshop (WAC7) (pp. 39-43).
Genre annotation
SUCHOMEL, Vít. Genre Annotation of Web Corpora: Scheme and Issues. In Kohei Arai, Supriya Kapoor, Rahul Bhatia. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 1. Vancouver, Canada: Springer Nature Switzerland AG, 2021. s. 738-754. ISBN 978-3-030-63127-7. doi:10.1007/978-3-030-63128-4_55.
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