K o CHET : A K orean Cultural Heritage Corpus for Entity-related Tasks (2022)

Abstract: As digitized traditional cultural heritage documents have rapidly increased, resulting in an increased need for preservation and management, practical recognition of entities and typification of their classes has become essential. To achieve this, we propose KoCHET - a Korean cultural heritage corpus for the typical entity-related tasks, i.e., named entity recognition (NER), relation extraction (RE), and entity typing (ET). Advised by cultural heritage experts based on the data construction guidelines of government-affiliated organizations, KoCHET consists of respectively 112,362, 38,765, 113,198 examples for NER, RE, and ET tasks, covering all entity types related to Korean cultural heritage. Moreover, unlike the existing public corpora, modified redistribution can be allowed both domestic and foreign researchers. Our experimental results make the practical usability of KoCHET more valuable in terms of cultural heritage. We also provide practical insights of KoCHET in terms of statistical and linguistic analysis. Our corpus is freely available at https://github.com/Gyeongmin47/KoCHET .

## introduction recently there has been an increasing interest in the preservation of national historical artifacts and traditional cultural heritage, and also grows up the importance of effective management of them through digitization and archival. as the amount of digitized information materials increases rapidly, information extraction (ie) tasks in natural language processing (nlp), such as named entity recognition (ner), relation extraction (re), and entity typing (et), have become an essential and fundamental step in the field of historical document analysis. despite the necessity of a well-refined entitycentric corpus specialized in domestic cultural her-itage, unfortunately, there no exists any cultural heritage domain-specialized corpus in korean. moreover, conventional entity-related systems deal only with a coarse set of entity types such as person, location, and organization which is significantly limited in terms of application @xcite . this absence of cultural heritage domain-specialized corpus and narrow coverage of entity types hinders the effective digitization of domestic historical documents because training the model with general corpus for entity-related tasks cannot afford to learn enough significant entity types such as pagodas, historical sites and intangible heritage, and their relations. furthermore, not in the cultural heritage domain, the existing entity-related datasets supervised by the public institutions have a complicated procedure for data acquisition, and they are also restricted from modification and redistribution. these cumbersome procedures and restrictions have been stumbling blocks for researchers against the rapid increase in digitized cultural heritage materials over the past few decades. to address these difficulties against the conservation of korean cultural heritage, we introduce a new dataset collection called kochet -korean cultural heritage corpus for entity-related tasks, a high-quality korean cultural heritage domainspecialized dataset for ner, re, and et tasks. for corpus construction, we crawled the e-museum digitized data of the national museum of korea 1 (including data from all 50 museums) as the source text which is for the interested public. we selectively used resources from the museums in which the details of artifacts were registered; moreover, for the completeness of the attribute data, we limited the chronological range of the data from the prehistoric era to the korean empire era, excluding the japanese colonial period. for the annotation, the categorization for classes and attributes appropriate was defined and developed following the 2020 named entity corpus research analysis 2 which was published under the guidelines as institutional organizations. as our corpus focuses on the entity features, it has more detailed and abundant entity types including diverse cultural heritage artifacts, compared to the existing accessible datasets that aim to deal with several downstream tasks in addition to entityrelated tasks. furthermore, the et of kochet is the first freely available corpus for the et task in korea. in addition to providing these values, this paper provides detailed statistics and linguistic analysis of kochet for each entity-related task to demonstrate their applicability and enhance understanding of the data, along with baseline experiments with language models. our contributions are summarized as follows: ## related works as domains that require expertise, such as the cultural heritage, contain entities or relationships that rarely appear in general domains, the necessity of a corpus specialized in the domain is obvious. despite such demand, korean does not yet have a corpus specialized in the cultural heritage area, unlike other languages. ## kochet following the guidelines of korean institutional organizations, kochet is a domain specialized corpus for cultural heritage, which ensures quality and can be freely accessed. in this section, we report the annotation process and guidelines in detail. ## experiment the detailed experimental settings are in appendix a. ## conclusion in this paper, we introduced kochet -a korean cultural heritage corpus for three typical entityrelated tasks, i.e., ner, re, and et. unlike the existing public korean datasets with additional restrictions, kochet obviated the cumbersome prerequisite and can be freely modified and redistributed. furthermore, we proved the applicability of our entity-abundant corpus with the experiments employing the various pre-trained language models and provided practical insights regarding the statistical, diachronic, and linguistic analysis. above all, the most significant contributing point is that the disclosure of our corpus is expected to serve as a cornerstone for the development of ie tasks for a traditional cultural heritage. we hope that the continuous effort to preserve cultural heritage with the effective management of digitized documents containing cultural artifacts is encouraged by this research.