86 results about "Semantic dependency" patented technology

The invention relates to a relation extraction method and system based on an attention cycle gated graph convolutional network, and the method comprises the steps of carrying out the semantic dependency analysis of a statement, enabling word embedding to be connected with a position feature, and obtaining a final word embedding representation; constructing a BLSTM network layer, and extracting a word context feature vector; applying an attention mechanism to the dependency tree to obtain a soft adjacency matrix of a fully connected graph with weight information; transmitting the word context feature vector and the soft adjacency matrix into a gated graph convolutional network, and extracting a high-order semantic dependence feature to obtain vector representation of a statement; and extracting vector representations of the two marked entities, splicing the extracted vector representations of the two marked entities with the vector representation of the statement, transmitting the spliced vector representation of the statement into a full connection layer of the gated graph convolutional network, calculating the probability of each relationship type and predicting the relationship type, and finally obtaining the relationship type of the statement. According to the invention, key information loss is avoided, and the relationship extraction performance is improved.

The invention discloses a text inference method based on limited semantic dependency analysis. The method comprises the following steps of: 1, according to a semantic dependency representation mechanism, establishing a Chinese text inference marking resource, wherein a text inference marking instance comprises a text T, a hypothesis H, a semantic dependency graph of the hypothesis and an inference type; 2, on the basis of the Chinese text inference marking resource, performing semantic dependency analysis on the hypothesis H which is newly input under the limitation of the text T which is newly input so as to judge whether the text T can infer the hypothesis H; and 3, evaluating, analyzing and summarizing an analysis process and a judgment result of the step 2, and improving the performance of the analysis process with feedback. By adoption of the method, the judgment of text inference is formalized into the problem of the limited semantic dependency analysis, and the text inference extends from entailment to preset and implication in type. The method contributes to processing of the inference of discourse and dialogue corpora which are relatively complicated.

The invention discloses an answer extraction method based on a semantic dependency tree. The method comprises the step of selecting an optimal answer from the candidate answer sentences by comprehensive consideration of a vector similarity, a word form similarity and a dependency path length similarity on the basis of considering a semantic relation between an interrogative sentences and candidateanswer sentences. According to the method, compared with other algorithm, the accurate rate for selection of the optimal answer sentence is greatly improved.

The invention relates to a visual angle level text sentiment classification method and system based on external knowledge, and the method comprises the steps: carrying out the characterization of a visual angle level text, and capturing a bidirectional semantic dependence relation of the text; combining the current word with an external knowledge synonym through a dynamic attention mechanism, andintroducing a sentinel vector to avoid misleading of external knowledge to the model; judging the contribution degree of each word to the view word through a position attention mechanism; calculatingan attention score of each memory content, nonlinearly combining the attention score of each layer with an output result of an upper layer by utilizing a threshold circulation unit, and taking the last layer as emotion feature representation of the text; and obtaining a final sentiment classification result by utilizing the classification function. According to the method, the view-level text sentiment classification performance can be improved, and the resource consumption can be reduced.

The invention relates to a Chinese structured event extraction method, and belongs to the technical field of information extraction. The Chinese structured event extraction method comprises the following steps of: performing syntactic dependency structure analysis on an unstructured text statement by using a syntactic dependency analysis tool to obtain a syntactic dependency analysis tree; analyzing the characteristics of the Chinese linguistic and syntactic dependency analysis tree, constructing a core verb chain, and identifying all events existing in the statement; adding a semantic dependency relationship to the syntactic dependency analysis tree by means of a semantic dependency analysis tool, and constructing a syntactic semantic dependency analysis tree; adjusting dependency structures of event core verbs, prepositions and passive language states in the syntactic semantic dependency analysis tree, and constructing a syntactic semantic dependency analysis event graph. According to the method, data does not need to be manually annotated, the structured event can be well extracted, and the extraction accuracy and recall rate are high.

The invention belongs to the technical field of intelligent services, and relates to a semantic recognition method for inscriptions on ancient bronze objects, which comprises the following steps of S1, performing pre-training on a BERT model by adopting an inscriptions-on-ancient-bronze-objects training set to obtain an inscriptions-on-ancient-bronze-objects enhanced context vector; s2, substituting the inscriptions-on-ancient-bronze-objects enhanced context vector into a BiLSTM model to obtain a inscriptions-on-ancient-bronze-objects implicit vector matrix H representing inscriptions-on-ancient-bronze-objects sentence context information; s3, performing semantic role identification and semantic dependency relationship identification on the inscriptions on ancient bronze objects accordingto the inscriptions-on-ancient-bronze-objects implicit vector matrix H; s4, establishing an inscriptions-on-ancient-bronze-objects knowledge graph according to the inscriptions-on-ancient-bronze-objects semantic role label and the semantic dependency relationship; and S5, substituting the to-be-identified inscriptions-on-ancient-bronze-objects into the inscriptions-on-ancient-bronze-objects knowledge graph for identification. The causal association of the inscriptions-on-ancient-bronze-objects description content and the semantic dependency relationship between semantic elements are comprehensively considered and fused, and the inscriptions-on-ancient-bronze-objects meaning can be understood through the context information, so that the recognition result is more accurate.