Unlocking K orean Verbs: A User-Friendly Exploration into the Verb Lexicon (2025)

Abstract: The Sejong dictionary dataset offers a valuable resource, providing extensive coverage of morphology, syntax, and semantic representation. This dataset can be utilized to explore linguistic information in greater depth.The labeled linguistic structures within this dataset form the basis for uncovering relationships between words and phrases and their associations with target verbs. This paper introduces a user-friendly web interface designed for the collection and consolidation of verb-related information, with a particular focus on subcategorization frames. Additionally, it outlines our efforts in mapping this information by aligning subcategorization frames with corresponding illustrative sentence examples.Furthermore, we provide a Python library that would simplify syntactic parsing and semantic role labeling. These tools are intended to assist individuals interested in harnessing the Sejong dictionary dataset to develop applications for Korean language processing.

## introduction when examining the verb lexicon for korean, the sejong dictionary has been a major language resource. as part of the 21st century sejong project, which aims to advance korean language information processing, the sejong dictionary has produced extensive datasets that describe korean lexicon data in great detail. although it is designed with a vast amount of morphological, semantic, and syntactic information, there have been minimal attempts to utilize its resources. this paper investigates the korean verb lexicon, with a particular focus on the subcategorization frames in the sejong verb dictionary. the objective is to facilitate easier access to and manipulation of the sejong dictionary, thus promoting further studies and applications in korean language processing. in annotating corpora with semantic roles, the methodology of proposition bank (propbank) has been widely adopted in natural language processing @xcite . similar efforts can be observed in the sejong dataset, which seeks to provide a meaningful level of linguistic representation and a corpus of annotated data to facilitate further research and analysis. this structured dataset will serve as a foundation for identifying relationships between words, such as organizing and searching for verbs that share the same subcategorization frames. within the sejong dictionary are xml files for each verb (figure 1 ). inside are xml tags that identify each word's morphological, semantic, and syntactic information with additional metadata. some annotations make it possible to identify arguments such as semantic roles of verbs in sentences (figure 2 ). a set of the underlying semantic roles for each verb and frame groupings are defined for each sense of the verb. then, in each group are the frames that annotate selection restrictions with example sentences. we believe this detailed verb representation level is vital for many language processing applications. with thorough and manual documentation on subcategorization in the sejong dictionary, we aim to enhance the dataset's usability, facilitating the creation of user-friendly systems for all future projects. in this paper, we introduce a web interface created for individuals with minimal programming experience or those seeking quick access to the verbs in the sejong dictionary. this interface consolidates verb information and provides easy access to subcategorization frames. it also includes our efforts to map information by projecting subcategorization frames onto corresponding sentence examples. additionally, we provide a python library that includes tools for syntactic parsing and semantic role labeling, designed for those who wish to utilize the sejong dictionary in developing korean figure 2 : example of subcategorziation frame to sentence projection language processing applications. therefore, our main contribution is two-fold: first, we offer a corpus of sentence examples from the sejong dictionary with annotated argument-predicate boundaries. second, we develop two key tools-a web interface and programming libraries-to facilitate access to sejong dictionary information. ## conclusion and future perspectives our current contributions, particularly the python library, have the potential to be applied across various linguistic tasks, including syntactic parsing systems that utilize lexical information, such as lexicalized parsers @xcite , semantic role labeling @xcite @xcite , and framenet parsing @xcite @xcite for the korean language. we are committed to broadening access to korean language data beyond traditional boundaries, offering a unified platform for linguists and computer scientists to explore the rich resources of the korean language. this platform will be invaluable for a wide range of korean language processing tasks and future linguistic research. we are continuously working on integrating additional korean verb lexicons, such as the korean propbank and framenet, into our web service. our ultimate goal is to develop a comprehensive korean verbnet. by systematically comparing verbs and their subcategorization frames across the sejong verb dictionary, propbank, and other resources-and resolving any discrepancies-we aim to harmonize frame information across our interfaces. this will offer users a more cohesive and seamless experience when exploring korean language data, contributing to advancements in korean linguistic research and natural language processing. our system, including its python library with sample verb files, can be accessed at http://117.17.185.27:8025/ .