Abstract
The diachronic evolution of word meaning has always been an important topic in linguistics, with new achievements in traditional linguistics. However, traditional “field work” can only be analyzed qualitatively, which needs accurate data collection and consumes a lot of manpower and material resources. In recent years, with the gradual rise of deep learning technology, more and more researchers have used distributed semantic representation to address semantic related problems. This new method not only opens up a new way of studying the semantic evolution of ancient Chinese, but also breaks the limitations of traditional linguistics. Under this background, this paper uses the BERT model, which is trained with the “Siku Quanshu” (Imperial Collection of Four) to get the distributed representation, (1) to practise the automatic annotation in ancient Chinese, with an accuracy of 92%; (2) to practise the automatic detection of semantic changes, including extension of meaning, synchronic distribution of meaning and diachronic evolution of meaning.
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National Language Commission Scientific Research Plan 2017 Key Project (ZDI135–42).
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Wang, H., Wang, L. (2021). A Research on the Evolution of Chinese Semantics Based on Distributed Representation. In: Liu, M., Kit, C., Su, Q. (eds) Chinese Lexical Semantics. CLSW 2020. Lecture Notes in Computer Science(), vol 12278. Springer, Cham. https://doi.org/10.1007/978-3-030-81197-6_61
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