4 results about "Word sense" patented technology

The application provides a word sense disambiguation method and device, wherein the method comprises the following steps: determining a to-be-disambiguated entity existing in to-be-disambiguated text and a corresponding candidate entity list based on an RPA knowledge graph; determining embedding features corresponding to each candidate entity in the candidate entity list and the to-be-disambiguated entity through RPA feature extraction based on each candidate entity and the to-be-disambiguated entity; and determining whether the to-be-disambiguated entity and the candidate entity are the same entity based on a word sense disambiguation model, the embedding features corresponding to each candidate entity, and the embedding features corresponding to the to-be-disambiguated entity. The application realizes the comparison of embedding features of the to-be-disambiguated text and the candidate text by comprehensively embedding entity features, entity context features and word features, determines whether the to-be-disambiguated entity and the candidate entity are the same entity, and obtains more rich and comprehensive text information, which is conducive to accurately analyzing the word sense and improving the word sense disambiguation accuracy.

The application discloses a similarity discrimination method and system for new word sense primitive recommendation, and comprises the following steps: in the HowNet word set, similar words to a new word are selected by a similarity discrimination model to form a similar word set; a local "word-semantic item-semantic primitive" relationship network is constructed according to all the words in the similar word set, the corresponding concept semantic items and semantic primitives of the words; semantic primitive nodes are selected based on a network node importance sorting method, a recommendation index of the semantic primitive nodes is generated according to the standardization degree centrality and the intermediate centrality of the semantic primitive nodes, the importance of the semantic primitive nodes is evaluated, the correlation between an unregistered word and a semantic primitive is established by taking the similar word set as a bridge, the sorting and selection of the candidate semantic primitives of the unregistered word are completed through the recommendation index, and the HowNet is expanded through the new word; the application effectively solves the similarity discrimination problem between the unregistered word and the word table word, and effectively solves the selection problem of the candidate semantic primitives.

Aiming at the defects of an existing test method in the field of word sense disambiguation test of machine translation in the aspects of triggering effective word sense conversion, maintaining original sense and maintaining semantic consistency, the invention provides a machine translation polysemous word translation evaluation method based on semantic item trigger word replacement. The method comprises the following steps: firstly, constructing a polysemy semantic item library, and screening source language sentences containing polysemy from a parallel corpus according to the semantic item library; performing natural language processing on the sentence, and identifying a trigger word of a polysemy special definition item in the sentence; replacing the trigger word with a replacement word to generate a variant sentence; performing machine translation and alignment on the original sentences and the variant sentences to obtain expressions of polysemy words in translations; and calculating the similarity of the polysemy translation expression, and judging whether a polysemy disambiguation error exists or not. Through a trigger word replacement strategy, a semantic controlled contrast sentence pair can be constructed, potential errors of a system in polysemous word translation are effectively revealed, and the pertinence and effectiveness of evaluation are improved.

The invention provides a traditional Chinese medicine cross-language aided translation system based on artificial intelligence, and belongs to the technical field of traditional Chinese medicine translation. The traditional Chinese medicine cross-language aided translation system based on artificial intelligence comprises a data acquisition module, a semantic recognition module, a semantic correction module, a translation strategy output module and a translation evaluation module. The system can track semantic distance changes between term translation and historical standards in real time, a translation migration file is established for recognized deviations, the corresponding relation between word meaning drift paths and contexts is recorded, the system can judge whether the deviations belong to common error types or not, rapid error correction is conducted on the basis of a term evolution database, and therefore the accuracy of term translation is improved. The mechanism does not depend on a fixed dictionary rule, but performs combined judgment according to factors such as a semantic change trend, a context structure adaptation degree and the frequency of historical deviation behaviors, so that the intelligence and the adaptability of deviation judgment are greatly improved, and the self-correction capability and the fault tolerance of a translation system are remarkably improved.