On the learnability of aspectual usage

Abstract We examine the learnability of grammatical aspect in Polish through the application of an error-correction learning algorithm to corpus data. We explore whether mastery of aspectual usage can be attained solely through exposure to co-occurrence patterns, or if an understanding of the abstract semantic distinctions discussed in the aspectual literature are a prerequisite. To validate the model, we compare the corpus-based findings with data on aspectual usage from a survey of Polish L1 users. Our findings show that aspectual preferences are best accounted for by a model that relies on co-occurrence information to predict a particular lemma, without reference to aspectual information. The models incorporating aspectual information, either by predicting aspect from co-occurrence information or from abstract semantic labels, performed adequately but were only able to capture usage preferences relating to one of the two aspects. This study contributes insights into the role of usage in the acquisition of linguistic categories and underscores the importance of integrating diverse evidence sources and methodologies for the development and validation of linguistic theories.

Authors

Institutions

Publication Details

Journal
Corpus Linguistics and Linguistic Theory
Published
2025-06-02
DOI
https://doi.org/10.1515/cllt-2023-0117
Citations
1
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
2.48

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the learnability of aspectual usage

Dagmar Divjak, Maciej Borowski, Petar Milin
1 citations
Corpus Linguistics and Linguistic Theory
Natural Language Processing Techniques
2.48
article

On the learnability of aspectual usage

Dagmar Divjak, Maciej Borowski, Petar Milin
article en
1 citations

Abstract

Abstract We examine the learnability of grammatical aspect in Polish through the application of an error-correction learning algorithm to corpus data. We explore whether mastery of aspectual usage can be attained solely through exposure to co-occurrence patterns, or if an understanding of the abstract semantic distinctions discussed in the aspectual literature are a prerequisite. To validate the model, we compare the corpus-based findings with data on aspectual usage from a survey of Polish L1 users. Our findings show that aspectual preferences are best accounted for by a model that relies on co-occurrence information to predict a particular lemma, without reference to aspectual information. The models incorporating aspectual information, either by predicting aspect from co-occurrence information or from abstract semantic labels, performed adequately but were only able to capture usage preferences relating to one of the two aspects. This study contributes insights into the role of usage in the acquisition of linguistic categories and underscores the importance of integrating diverse evidence sources and methodologies for the development and validation of linguistic theories.

Corpus Linguistics and Linguistic Theory
University of Birmingham (GB)
Leverhulme Trust
Openalex Percentile: Top 10%
Natural Language Processing Techniques
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

On the learnability of aspectual usage — Dagmar Divjak, Maciej Borowski, et al. · Corpus Linguistics and Linguistic Theory (2025) | TGRS Research Map | TGRS