Evaluating and automating the annotation of a learner corpus

Alexandr Rosen; Jirka Hana; Barbora Štindlová; Anna Feldman

doi:10.1007/s10579-013-9226-3

Evaluating and automating the annotation of a learner corpus

Alexandr Rosen, Jirka Hana, Barbora Štindlová, Anna Feldman

Linguistics

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

Abstract

The paper describes a corpus of texts produced by non-native speakers of Czech. We discuss its annotation scheme, consisting of three interlinked tiers, designed to handle a wide range of error types present in the input. Each tier corrects different types of errors; links between the tiers allow capturing errors in word order and complex discontinuous expressions. Errors are not only corrected, but also classified. The annotation scheme is tested on a data set including approx. 175,000 words with fair inter-annotator agreement results. We also explore the possibility of applying automated linguistic annotation tools (taggers, spell checkers and grammar checkers) to the learner text to support or even substitute manual annotation.

Original language	English
Pages (from-to)	65-92
Number of pages	28
Journal	Language Resources and Evaluation
Volume	48
Issue number	1
DOIs	https://doi.org/10.1007/s10579-013-9226-3
State	Published - Mar 2014

Keywords

Czech
Error annotation
Learner corpus
Second language acquisition

Access to Document

10.1007/s10579-013-9226-3

Cite this

@article{7651cd722bd14e7a9ab10a6d90507a72,

title = "Evaluating and automating the annotation of a learner corpus",

abstract = "The paper describes a corpus of texts produced by non-native speakers of Czech. We discuss its annotation scheme, consisting of three interlinked tiers, designed to handle a wide range of error types present in the input. Each tier corrects different types of errors; links between the tiers allow capturing errors in word order and complex discontinuous expressions. Errors are not only corrected, but also classified. The annotation scheme is tested on a data set including approx. 175,000 words with fair inter-annotator agreement results. We also explore the possibility of applying automated linguistic annotation tools (taggers, spell checkers and grammar checkers) to the learner text to support or even substitute manual annotation.",

keywords = "Czech, Error annotation, Learner corpus, Second language acquisition",

author = "Alexandr Rosen and Jirka Hana and Barbora {\v S}tindlov{\'a} and Anna Feldman",

year = "2014",

month = mar,

doi = "10.1007/s10579-013-9226-3",

language = "English",

volume = "48",

pages = "65--92",

journal = "Language Resources and Evaluation",

issn = "1574-020X",

publisher = "Springer Netherlands",

number = "1",

}

TY - JOUR

T1 - Evaluating and automating the annotation of a learner corpus

AU - Rosen, Alexandr

AU - Hana, Jirka

AU - Štindlová, Barbora

AU - Feldman, Anna

PY - 2014/3

Y1 - 2014/3

N2 - The paper describes a corpus of texts produced by non-native speakers of Czech. We discuss its annotation scheme, consisting of three interlinked tiers, designed to handle a wide range of error types present in the input. Each tier corrects different types of errors; links between the tiers allow capturing errors in word order and complex discontinuous expressions. Errors are not only corrected, but also classified. The annotation scheme is tested on a data set including approx. 175,000 words with fair inter-annotator agreement results. We also explore the possibility of applying automated linguistic annotation tools (taggers, spell checkers and grammar checkers) to the learner text to support or even substitute manual annotation.

AB - The paper describes a corpus of texts produced by non-native speakers of Czech. We discuss its annotation scheme, consisting of three interlinked tiers, designed to handle a wide range of error types present in the input. Each tier corrects different types of errors; links between the tiers allow capturing errors in word order and complex discontinuous expressions. Errors are not only corrected, but also classified. The annotation scheme is tested on a data set including approx. 175,000 words with fair inter-annotator agreement results. We also explore the possibility of applying automated linguistic annotation tools (taggers, spell checkers and grammar checkers) to the learner text to support or even substitute manual annotation.

KW - Czech

KW - Error annotation

KW - Learner corpus

KW - Second language acquisition

UR - http://www.scopus.com/inward/record.url?scp=84897020402&partnerID=8YFLogxK

U2 - 10.1007/s10579-013-9226-3

DO - 10.1007/s10579-013-9226-3

M3 - Article

AN - SCOPUS:84897020402

SN - 1574-020X

VL - 48

SP - 65

EP - 92

JO - Language Resources and Evaluation

JF - Language Resources and Evaluation

IS - 1

ER -

Evaluating and automating the annotation of a learner corpus

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this