Error Tagging in the Lithuanian Learner Corpus

Ruzaitė, Jūratė; Dereškevičiūtė, Sigita; Kavaliauskaitė-Vilkinienė, Viktorija; Krivickaitė-Leišienė, Eglė

doi:10.3233/faia200631

Frontiers in Artificial Intelligence and Applications

2020

DOI: 10.3233/faia200631

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Error Tagging in the Lithuanian Learner Corpus

Jūratė Ruzaitė¹,

Sigita Dereškevičiūtė²,

Viktorija Kavaliauskaitė-Vilkinienė³

et al.

Abstract: This paper is a work-in-progress report on error annotation in the Lithuanian Learner Corpus (LLC), which has been developed using the TEITOK environment. The LLC is the first electronic corpus of learner Lithuanian that represents learners of very diverse native language backgrounds and different proficiency levels. In this paper, we have a double aim: firstly, we present the structure of the corpus in its current state; and secondly, we describe the main principles, procedures, and challenges of error annota… Show more

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2022

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A New Corpus-Driven Lexical Database for Lithuanian as a Foreign Language

Kovalevskaitė

Rimkutė

2022

Sustainable Multilingualism

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Summary In this paper, we describe a new lexicographic resource for advanced learners of Lithuanian, the Lexical Database of Lithuanian Language Usage, which is the first attempt in Lithuanian lexicography to prepare a description of vocabulary based on the word usage analysis in the particular corpus. The written subpart of the Lithuanian Pedagogic Corpus (approx. 620,000 tokens) was used to develop headword lists and collect word usage information in the form of corpus patterns. In the database, there are 3,700 lexical items, words and multi-word units (compounds, idioms or sayings). For the appr. 700 most frequent words from a shared vocabulary (they appear in texts assigned to A1, A2, B1 and B2 levels, and their frequency in the whole corpus is 100 occurrences and above), we prepared a full-record entry: it includes sense-related corpus patterns with grammatical, semantic and lexical information and the examples illustrating all pattern components. The short-record entry (no patterns, only examples) is prepared for the less frequent words from the shared vocabulary, which are derivationally related to the most frequent headwords. The users are provided with 2,542 derivatives, which are linked to 940 headwords. In the database, 28,550 encoding examples are manually selected for all 3,000 headwords and 700 phrases. We discuss the features of the database, and, particularly, the adopted semi-automated procedure of Corpus Pattern Analysis, which was used for the description of word usage. We evaluate the approach applied, and discuss its advantages for users as well as provide the suggestions for the future improvements of the resource, which can be used as an additional resource in the classroom of Lithuanian as a foreign language, and, together with the available corpora, fill in a gap of usage information in the existing (learner) dictionaries.

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A New Corpus-Driven Lexical Database for Lithuanian as a Foreign Language

Kovalevskaitė

Rimkutė

2022

Sustainable Multilingualism

View full text Add to dashboard Cite

show abstract

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Error Tagging in the Lithuanian Learner Corpus

Cited by 1 publication

References 3 publications

A New Corpus-Driven Lexical Database for Lithuanian as a Foreign Language

A New Corpus-Driven Lexical Database for Lithuanian as a Foreign Language

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