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A Method of Event Argument Role Extraction Based on Multi-Head Attention Mechanism

An attention and argument technology, which is applied in unstructured text data retrieval, instrumentation, text database indexing, etc., and can solve problems such as argument role extraction errors.

Active Publication Date: 2020-04-07
温州开晨科技有限公司
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AI Technical Summary

Problems solved by technology

[0003] Aiming at the problem that there are errors in the extraction of argument roles when there are multiple events in a sentence in event argument role extraction, the present invention discloses an event argument role extraction method based on a multi-head attention mechanism

Method used

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  • A Method of Event Argument Role Extraction Based on Multi-Head Attention Mechanism
  • A Method of Event Argument Role Extraction Based on Multi-Head Attention Mechanism
  • A Method of Event Argument Role Extraction Based on Multi-Head Attention Mechanism

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Embodiment

[0064] Obtain the event text to be extracted, and perform word segmentation processing on the text. After processing, the words are converted into word vectors through the trained word2vec model. Input the trained bidirectional GRU neural network to obtain the extracted event trigger words and corresponding event types.

[0065] Such as figure 1 , using the processed word vector and the corresponding label input to fuse the network of the multi-head supervisory attention mechanism, initialize the neural network parameters with the obtained weight, and adjust the neuron's weight through BP backpropagation according to the GRU part and the attention mechanism part. weights, to obtain a trained bidirectional GRU neural network with synergistic contextual attention. And use the trained two-way GRU model to process the event text to be extracted. Specific steps include:

[0066] Input the preprocessed training text (word vector and corresponding event annotation) into the bidir...

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Abstract

The invention discloses an event argument role extraction method based on a multi-head attention mechanism. The present invention realizes steps as follows: step (1) data set text preprocessing, output preprocessed text and corresponding label; Semantic dependency analysis, outputting the semantic dependency path between the trigger word and the candidate argument; step (4) inputting the preprocessed text into the network in step (2) and outputting the encoding of each word after the network training, in the fusion step (3) The semantic dependency path output of <触发词编码，候选论元编码，语义依存路径>Argument classification structure; Step (5) Input the argument classification structure into the classification network for training and classification. The present invention analyzes the text by using the neural network method fused with the multi-head supervisory attention mechanism, and has a good ability of extracting the role of the argument when there are multiple events in the event sentence.< / 触发词编码，候选论元编码，语义依存路径>

Description

technical field [0001] The invention belongs to the technical field of natural language processing, relates to a method for classifying event argument roles, and provides an event argument role extraction method based on a multi-head attention mechanism. It is specifically used to extract event-related arguments from unstructured text and determine the role of arguments in the event. Background technique [0002] Event argument role extraction is to extract event-related information elements from unstructured information, and complete the event in a structured form. The current main research methods are pattern matching and machine learning. Pattern matching can achieve high performance in specific fields, but poor portability. Compared with pattern matching, machine learning has nothing to do with the domain, does not require too much guidance from domain experts, and has better system portability. With the construction of related corpora and the continuous enrichment of...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/31G06F40/30G06F16/35
CPCG06F16/313G06F16/353G06F40/30
Inventor 汤景凡戚铖杰张旻姜明闻涛
Owner 温州开晨科技有限公司
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