Article | Proceedings of the 7th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2018) at SLTC, Stockholm, 7th November 2018 | Normalization in Context: Inter-Annotator Agreement for Meaning-Based Target Hypothesis Annotation Linköping University Electronic Press Conference Proceedings
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Title:
Normalization in Context: Inter-Annotator Agreement for Meaning-Based Target Hypothesis Annotation
Author:
Adriane Boyd: Department of Linguistics, University of T¨ubingen, Germany
Download:
Full text (pdf)
Year:
2018
Conference:
Proceedings of the 7th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2018) at SLTC, Stockholm, 7th November 2018
Issue:
152
Article no.:
002
Pages:
10-22
No. of pages:
13
Publication type:
Abstract and Fulltext
Published:
2018-11-02
ISBN:
978-91-7685-173-9
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
NEALT Proceedings Series
Publisher:
Linköping University Electronic Press, Linköpings universitet


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We explore the contribution of explicit task contexts in the annotation of word-level and sentence-level normalizations for learner language. We present the annotation schemes and tools used to annotate both word- and sentence-level target hypotheses given an explicit task context for the Corpus of Reading Exercises in German (Ott et al., 2012) and discuss a range of inter-annotator agreement measures appropriate for evaluating target hypothesis and error annotation.

For learner answers to reading comprehension questions, we find that both the amount of task context and the correctness of the learner answer influence the inter-annotator agreement for word-level normalizations. For sentence-level normalizations, the teachers’ detailed assessments of the learner answer meaning provided in the corpus give indications of the difficulty of the target hypothesis annotation task. We provide a thorough evaluation inter-annotator agreement for multiple aspects of meaning-based target hypothesis annotation in context and explore metrics beyond inter-annotator agreement that can be used to evaluate the quality of normalization annotation.



Keywords: normalization, target hypothesis annotation, reliability of annotation

Proceedings of the 7th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2018) at SLTC, Stockholm, 7th November 2018

Author:
Adriane Boyd
Title:
Normalization in Context: Inter-Annotator Agreement for Meaning-Based Target Hypothesis Annotation
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Proceedings of the 7th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2018) at SLTC, Stockholm, 7th November 2018

Author:
Adriane Boyd
Title:
Normalization in Context: Inter-Annotator Agreement for Meaning-Based Target Hypothesis Annotation
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