Building K orean A bstract M eaning R epresentation Corpus (2020)

Abstract: To explore the potential sembanking in Korean and ways to represent the meaning of Korean sentences, this paper reports on the process of applying Abstract Meaning Representation to Korean, a semantic representation framework that has been studied in wide range of languages, and its output: the Korean AMR corpus. The corpus which is constructed so far is a size of 1,253 sentences and its raw texts are from ExoBrain Corpus, a state-led R&D project on language AI. This paper also analyzes the result in both qualitative and quantitative manners, proposing discussions for further development.

## introduction this paper aims to prepare the annotation guideline for applying abstract meaning representation (amr)-the annotation framework to represent the meaning of the sentence in a graph structure-to korean and construct a corpus based on it as well as to explore the possibility of new korean semantic annotation methodologies and language resources. until now, the field of korean natural language processing attempts to construct a corpus targeted to specific phenomena such as polysemy disambiguation, named entities, temporal and spatial information and semantic roles. however, given the complex relationship between the expression and its meaning, integrated meaning representation system and language resources that far exceed the fragmented analysis are necessary. in response, this study creates annotation guidelines covering sentence structure and grammatical phenomenon in korean and describes the following result, a korean amr corpus with a size of 1,253 sentences. korean amr uses predicate frames from korean propbank @xcite to represent the relation between events and concepts. parts of the procedures are automated by using feature annotation form preconstructed parallel corpus. as a result, the search cost has been reduced and the annotation process has been simplified. section 4 will analyze the corpus in qualitative and quantitative perspectives and provide insight for further research. @xcite in 2016, annotation specification for chinese amr (camr) and the chinese version of the little prince corpus was released. @xcite according to @xcite and @xcite , the currently known size of chinese amr bank is 10,149 sentences; such a size can be said to approach the level that allows a significant parsing ability. follow-up efforts have since continued, including @xcite , which attempted to expand predicate lexicon in order to improve the chinese amr. research efforts based on the little prince corpus act as a 'calling water' in the multilingual amr studies. in spanish, a basic research was performed on how to represent grammatical phenomena that are characteristic of individual languages based on amr @xcite ; in brazilian portuguese, the little prince corpus (amr-br) was constructed @xcite , laying the foundations for the construction of the general-purpose corpus. (sobrevilla cabezudo and pardo, 2019) amr-based studies that aim to develop semantic representation resources have been done in vietnamese @xcite and turkish @xcite as well. in korean, preliminary studies have been done to illustrate some grammatical phenomena that are unique to korean, such as copula construction, its negation, and case-stacking, and address how they can be represented within the grammatical system of amr. @xcite further studies have developed a korean guideline v1.0, thereby laying the foundations for corpus construction. @xcite this study expands upon the aforementioned studies by discussing the process and outcomes of the construction of korean amr corpus. ## challenges on korean sembanking for korean amr to be actually applied to systems that understand and process the natural language, beyond specific tasks such as semantic parsing, there are many challenges to overcome. the korean amr corpus presented in this paper is in small size with less specific guidelines. therefore, it is necessary to set specific goals for both the quality and quantity aspects of data. the first challenge that korean amr is facing is developing several supporting resources for the annotation while simultaneously revising guidelines. to provide more precise meaning representation, ambiguous descriptions in the guideline must be changed to concrete wordings and extensive examples. moreover, the korean propbank should expand its predicates lexicon with enlarged multi-word expression, such as collocation and idioms. the second challenge is quantitative expansion. to overcome lack of training data, integrated annotation environment that reduces search cost and fosters more intuitive annotation is required, and part of the annotation procedures must be automated to simplify the entire process. ## conclusion this paper introduced the procedure for building a korean amr corpus, discussing several issues for further development. the korean amr corpus for this study is a size of 1,253 sentences, serving as the first result of foundational studies. even with small size, the korean amr corpus will be the source of empirical clues for developing korean amr. it will contribute to laying the foundation for future applications of natural language understanding and generation.