MorfFlex: Handling Rich Morphology

2026-06-23

AI Summary

This work addresses the challenges posed by morphologically rich languages such as Czech, where extensive inflectional and derivational morphology leads to unwieldy lexicon sizes and difficulties in ensuring annotation consistency. To tackle these issues, the authors propose MorfFlex, an architecture that explicitly models inflectional and derivational rules through a system of structured pattern rules operating on <word form, lemma, part-of-speech> triples. By leveraging hand-curated source files and transformation scripts, MorfFlex compresses massive word-form inventories into a compact, manageable lexical resource. The resulting MorfFlex CZ dictionary encompasses over 100 million word forms and one million lemmas, drastically reducing storage requirements while supporting consistent annotation in the Prague Dependency Treebank and enabling high-quality NLP tools such as MorphoDiTa.

Abstract

We present MorfFlex, a morphological dictionary architecture suitable for languages with extensive regularity in both inflection and derivation. As the primary example of MorfFlex in use we introduce MorfFlex CZ, a morphological dictionary of Czech. It is distributed as a simple, unstructured list of <wordform, lemma, tag> triplets, however, its manually maintained, unpublished source files and conversion scripts encode a sophisticated system of inflectional and derivational patterns. These patterns dramatically reduce the otherwise enormous size of the dictionary, which currently contains over 100 million wordforms and more than 1 million lemmas. The MorfFlex CZ dictionary serves as an essential resource for ensuring the consistency of manual morphological annotation in the Prague Dependency Treebanks and underpins state-of-the-art automatic tools such as MorphoDiTa. In this paper, we focus on: (i) presenting an effective method for managing the rich morphological system within the dictionary, and (ii) demonstrating the utility of such a language resource for maintaining annotation consistency in corpora and supporting the development of advanced NLP applications.

Problem

• morphology
• inflection
• derivation
• lexical resource
• morphological dictionary

Innovation

• morphological dictionary
• inflectional patterns
• derivational morphology
• annotation consistency
• NLP resource