Abstract
Tang poetry is an important aspect of ancient Chinese culture. Given that Tang poetry has unique features in text structure, how to use entity recognition, knowledge graph and other information processing technologies to research poetry is of great importance. However, the existing artificial neural network methods for named entity recognition require a large number of labeled training sets, while Chinese Tang poetry has not been labeled with a good training set. Besides, the grammatical structure of Tang poetry is far from modern Chinese. Therefore, for place name recognition in poetry, the existing neural network methods do not perform well. This article studies and analyzes the metrical form of Tang poetry, finds the metrical rules of place names, and summarizes the feature templates based on the metrical rules. According to the feature templates of Tang poetry, a method of combining feature templates with conditional random field is proposed. Experimental results prove the effectiveness of the proposed method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. LingvisticÃę Investigationes 30(1), 3–26 (2007)
Wang, Y., Xia, B., Liu, Z., Li, Y., Li, T.: Named entity recognition for Chinese telecommunications field based on Char2Vec and Bi-LSTMs. In: ISKE, pp. 1–7 (2017)
Lin, B.Y., Xu, F.F., Luo, Z., Zhu, K.Q.: Multi-channel BiLSTM-CRF model for emerging named entity recognition in social media. In: NUT@EMNLP, pp. 160–165 (2017)
Guohua, W., Tang, G., Wang, Z.: An attention-based BiLSTM-CRF model for Chinese clinic named entity recognition. IEEE Access 7, 113942–113949 (2019)
Huang, S., Wang, D., He, L.: Research on the construction of automatic recognition model of ancient Chinese place names based on pre-qin corpus. Library Inf. Serv. 59(12), 135–140 (2015)
Li, N.: Construction of automatic recognition model for place names of local records and ancient books in the library based on digital culture. Library 2018(05), 67–73 (2018)
Poostchi, H., Borzeshi, E.Z.: BiLSTM-CRF for Persian named-entity recognition ArmanPersoNERCorpus: the first entity-annotated Persian dataset. In: LREC (2018)
Wei, J.,: Symbiosis and reorganization of Yu Wensuo’s translation of tang poetry. Foreign Lang. Foreign Lang. Teach. 2019(05), 126–134 + 151 (2019)
Chen, G.: The monument of Tang poetry: “Nine families annotate Du’s Poetry”. In: Learning Times, 13 Sept 2019. (006)
Yang, F., Zhao, J., Zou, B.: CRFs-based named entity recognition incorporated with heuristic entity list searching. In: IJCNLP 2008, pp. 171–174 (2008)
Das, A., Garain, U.: CRF-based named entity recognition @ICON 2013. CoRR abs/1409.8008 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhang, Y., Li, Y., Zhang, J., Ye, Y. (2020). A Method for Place Name Recognition in Tang Poetry Based on Feature Templates and Conditional Random Field. In: Wang, X., Zhang, R., Lee, YK., Sun, L., Moon, YS. (eds) Web and Big Data. APWeb-WAIM 2020. Lecture Notes in Computer Science(), vol 12317. Springer, Cham. https://doi.org/10.1007/978-3-030-60259-8_46
Download citation
DOI: https://doi.org/10.1007/978-3-030-60259-8_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-60258-1
Online ISBN: 978-3-030-60259-8
eBook Packages: Computer ScienceComputer Science (R0)