Z i N et: L inking C hinese Characters Spanning Three Thousand Years (2022)

Abstract: Modern Chinese characters evolved from 3,000 years ago. Up to now, tens of thousands of glyphs of ancient characters have been discovered, which must be deciphered by experts to interpret unearthed documents. Experts usually need to compare each ancient character to be examined with similar known ones in whole historical periods. However, it is inevitably limited by human memory and experience, which often cost a lot of time but associations are limited to a small scope. To help researchers discover glyph similar characters, this paper introduces ZiNet, the first diachronic knowledge base describing relationships and evolution of Chinese characters and words. In addition, powered by the knowledge of radical systems in ZiNet, this paper introduces glyph similarity measurement between ancient Chinese characters, which could capture similar glyph pairs that are potentially related in origins or semantics. Results show strong positive correlations between scores from the method and from human experts. Finally, qualitative analysis and implicit future applications are presented.

## introduction the evaluation of chinese character can be divided into two stages: the ancient stage (before han dynasty, 202 bc) and the clerical and standard script stage (after han dynasty) @xcite . at the former stage, ancient characters do not have a fixed shape, and their glyphs show several differences respect to modern characters: representatives include the oracle bone script (oracle) in the shang dynasty (about 1300 bc), which appears on animal bones or turtle shells @xcite , the chinese bronze script (bronze, about 1000 bc) appeared on bronze wares @xcite 400 bc) @xcite . evolution of glyphs of chinese characters can be observed in figure 1 . ancient unearthed documents show a wealth of information regarding that historical periods @xcite @xcite , which is great significant for understanding the culture and history of china, as well as the whole world. nevertheless, nearly half of ancient characters cannot be deciphered yet. the purpose of deciphering ancient character is to find the modern chinese characters evolved from it and give enough interpretations and evidences in terms of glyphs, phonetics and semantics. according to the systematic nature and evolution law of chinese characters, experts need to compare the character to be examined with similar known characters in history. however, there are tens of thousands of glyphs of characters appeared in history, discovering similar character heavily relies on expert experience, which is inevitably limited by human memory and reduces the comprehensiveness and efficiency. to measure similarity between ancient characters, automatic methods face challenges: (1) it lacks available resources of ancient chinese, which means existing algorithms, especially supervised al-gorithms cannot be directly used to solve this problem. and ancient characters do not have features such as standard code, pinyin and strokes, which have been widely used for describing the modern one. (2) it is complicated to represent and measure ancient characters. for instance, edit distance is widely used to measure orthographic similarity between words in romance languages; however, it is not suitable for measuring glyph similarity between pictographic chinese characters. based on above considerations, the main contributions of this paper are: (1) introduces zinet, the first diachronic knowledge base for linking chinese characters and words across various historical periods. (2) as the first application of zinet, this paper introduces methods for glyph similarity measurement, which aims at giving glyph similar scores for ancient chinese character pairs. there are two main characteristics of zinet comparing to existing lexical resources: (1) it is designed based on the systematic nature of chinese characters. the smallest unit of zinet is the radical, the component of character, which is of significance for analyzing semantics or phonics of characters (details will be discussed in section 3.1). the paper is organized as follows: section 2 presents the state of the art; section 3 describes key information of zinet; section 4 describes glyph similarity measurement; results are proposed in section 5; section 6 shows implications and future works; section 7 concludes the paper and section 8 shows ethics. ## implications and future work this work firstly put forward a diachronic chinese lexical resource, which expanded the architecture of princeton wordnet by adding several layers to describe diachronic characters under the lexical layer. word was regarded as the basic unit in most existing semantic lexical databases @xcite @xcite ; however, based on our investigations, glyphs or radicals of chinese characters can also show semantics, which have been used to enrich input information in several nlp tasks @xcite @xcite . besides, in interdisciplinary researches with historical linguistics, chinese history and paleography, etc., diachronic characters and words, glyphs and semantics were always discussed together because of their close links, while in the low-resources background, existing nlp algorithms have not been widely applied in these fields. the significance of zinet is to give a more complete architecture to support diverse nlp tasks: it introduces not only lexical, but also glyph and character information, not only works for modern chinese, but also ancient chinese, or regarding them in the same diachronic space. we hope this work can enlighten diversity of the architecture of language resources and promote development of more nlp tasks in interdisciplinary researches. at the application level, zinet hold potential for knowledge powered chinese nlp and image processing algorithms, especially in interdisciplinary researches, such as cognate discovery, word sense tracking and rubbing character recognition. zinet can also support platforms and provide experts in related fields with domain knowledge and quick information suggestions. for instance, giving retrievals of the evolution timeline of characters and words, annotated unearth document corpus and recommendations of similar characters at various historical times. in future work, zinet will be further expanded to other historical periods, and synsets will be linked into conceptual ontology layer to describe the topics of chinese in varied historical periods. in application level, we will apply zinet in other knowledge powered tasks, for instance, using radical knowledge to enhance performance of ancient character image recognition. and we will further explore that how it can help research and decipher ancient characters. meanwhile, we are developing a platform to support services of zinet, which will be open in near future. ## conclusion this paper proposed zinet, a diachronic chinese knowledge base, which is the first structured resource dedicated to describe the relations, and evolution of chinese characters and words. based on zinet, we demonstrated methods for calculating glyph similarity between ancient chinese characters. results show a strong positive correlation between the scores obtained from our method and from experts. we hope this work can serve experts in chinese linguistics, history and related fields.