Name
Abstract | ||
|---|---|---|
AbstractFrequently corresponding to syntactic components, the Maximal-length Noun Phrase (MNP) possesses abundant syntactic and semantic information and acts a certain semantic role in sentences. Recognition of MNP plays an important role in Natural Language Processing and lays the foundation for analyzing and understanding sentence structure and semantics. By comparing the essence of different MNPs, this article defines the MNP in the Tibetan language from the perspective of syntax tree. A total of 6,038 sentences are extracted from the syntax tree corpus, the structure type, boundary feature, and frequency of MNPs are analyzed, and the MNPs are recognized by applying the sequence tagging model and the syntactic analysis model. The accuracy, recall, and F1 score of the recognition results of applying sequence tagging model are 87.14%, 84.72%, and 85.92%, respectively. The accuracy, recall, and F1 score of the recognition results of applying syntactic analysis model are 87.66%, 87.63%, and 87.65%, respectively. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3423324 | ACM Transactions on Asian and Low-Resource Language Information Processing |
Keywords | DocType | Volume |
Tibetan syntax tree, the Maximal-length Noun Phrase, type of noun phrase | Journal | 20 |
Issue | ISSN | Citations |
2 | 2375-4699 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Congjun Long | 1 | 8 | 4.67 |
| Xuewen Zhou | 2 | 0 | 1.01 |
| Maoke Zhou | 3 | 0 | 0.34 |