How lemmatisation and derivational annotation affect productivity measures: The case of deverbal agent nouns in the Joint Corpus of Lithuanian

We discuss the automatic and manual stages of the lemmatisation and annotation of the Joint Corpus of Lithuanian (1.3 billion words) used to measure derivational productivity. As a case study, we present data of three productive deverbal agent noun suffixes in Lithuanian, -toj-, -ėj-, -ik-, and measure their realized, expanding, and potential productivity. We show that an additional semi-automatic lemmatisation and a manual derivational annotation significantly increase type and hapax counts. We also note that lemmatisation is affected by an artificially increased number of lemmas due to homographic forms unresolved by the lemmatiser. After the manual disambiguation of hapaxes, the numbers of feminine formations in -toj-(a) and -ėj-(a) were the most significantly reduced.

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Publication Details

Journal
Valoda nozīme un forma / Language Meaning and Form
Published
2024-12-16
DOI
https://doi.org/10.22364/vnf.15.09
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

How lemmatisation and derivational annotation affect productivity measures: The case of deverbal agent nouns in the Joint Corpus of Lithuanian

Agnė Navickaitė-Klišauskienė, Virginijus Dadurkevičius, Jurgis Pakerys
Valoda nozīme un forma / Language Meaning and Form
Natural Language Processing Techniques
article

How lemmatisation and derivational annotation affect productivity measures: The case of deverbal agent nouns in the Joint Corpus of Lithuanian

Agnė Navickaitė-Klišauskienė, Virginijus Dadurkevičius, Jurgis Pakerys
article en

Abstract

We discuss the automatic and manual stages of the lemmatisation and annotation of the Joint Corpus of Lithuanian (1.3 billion words) used to measure derivational productivity. As a case study, we present data of three productive deverbal agent noun suffixes in Lithuanian, -toj-, -ėj-, -ik-, and measure their realized, expanding, and potential productivity. We show that an additional semi-automatic lemmatisation and a manual derivational annotation significantly increase type and hapax counts. We also note that lemmatisation is affected by an artificially increased number of lemmas due to homographic forms unresolved by the lemmatiser. After the manual disambiguation of hapaxes, the numbers of feminine formations in -toj-(a) and -ėj-(a) were the most significantly reduced.

Valoda nozīme un forma / Language Meaning and Form
Vilnius University (LT), Vytautas Magnus University (LT)
Decent work and economic growth
Openalex Percentile: Top 79%
Natural Language Processing Techniques
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