POMIKÁLEK, Jan, Pavel RYCHLÝ and Miloš JAKUBÍČEK. Building a 70 billion word corpus of English from ClueWeb. In Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12). Istanbul, Turkey: European Language Resources Association (ELRA), 2012, p. 502-506. ISBN 978-2-9517408-7-7.
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Basic information
Original name Building a 70 billion word corpus of English from ClueWeb
Authors POMIKÁLEK, Jan (203 Czech Republic, belonging to the institution), Pavel RYCHLÝ (203 Czech Republic, belonging to the institution) and Miloš JAKUBÍČEK (203 Czech Republic, guarantor, belonging to the institution).
Edition Istanbul, Turkey, Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12), p. 502-506, 5 pp. 2012.
Publisher European Language Resources Association (ELRA)
Other information
Original language English
Type of outcome Proceedings paper
Field of Study Informatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW URL
RIV identification code RIV/00216224:14330/12:00057572
Organization Fakulta informatiky – Repository – Repository
ISBN 978-2-9517408-7-7
UT WoS 000323927700080
Keywords in English corpus; clueweb; English; encoding; word sketch
Links GAP401/10/0792, research and development project. LM2010013, research and development project. 248307, interní kód Repo.
Changed by Changed by: RNDr. Daniel Jakubík, učo 139797. Changed: 1/9/2020 12:48.
Abstract
This work describes the process of creation of a 70 billion word text corpus of English. We used an existing language resource, namely the ClueWeb09 dataset, as source for the corpus data. Processing such a vast amount of data presented several challenges, mainly associated with pre-processing (boilerplate cleaning, text de-duplication) and post-processing (indexing for efficient corpus querying using the CQL – Corpus Query Language) steps. In this paper we explain how we tackled them: we describe the tools used for boilerplate cleaning (jusText) and for de-duplication (onion) that was performed not only on full (document-level) duplicates but also on the level of near-duplicate texts. Moreover we show the impact of each of the performed pre-processing steps on the final corpus size. Furthermore we show how effective parallelization of the corpus indexation procedure was employed within the Manatee corpus management system and during computation of word sketches (one-page, automatic, corpus-derived summaries of a word’s grammatical and collocational behaviour) from the resulting corpus.
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