Relation Extraction Model Based on Semantic Enhancement Mechanism

Relational extraction is one of the basic tasks related to information extraction in natural language processing, and is an important link and core task in the fields of information extraction, natural language understanding, and information retrieval. None of the existing relation extraction method...

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Published in:2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS) pp. 1 - 7
Main Authors: Liu, PeiYu, Du, JunPing, Shao, YingXia, Guan, Zeli
Format: Conference Proceeding
Language:English
Published: IEEE 22.09.2023
Subjects:
Attention mechanism
Complex systems
Data mining
Encoding
Natural language processing
Relation extraction
Semantic enhancement
Semantic similarity
Semantics
Subject lexicon
Task analysis
Vocabulary
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Abstract Relational extraction is one of the basic tasks related to information extraction in natural language processing, and is an important link and core task in the fields of information extraction, natural language understanding, and information retrieval. None of the existing relation extraction methods can effectively solve the problem of triple overlap. The CasAug model proposed in this paper based on the CasRel framework combined with the semantic enhancement mechanism can solve this problem to a certain extent. The CasAug model enhances the semantics of the identified possible subjects by adding a semantic enhancement mechanism, First, based on the semantic coding of possible subjects, pre-classify the possible subjects, and then combine the subject lexicon to calculate the semantic similarity to obtain the similar vocabulary of possible subjects. According to the similar vocabulary obtained, each word in different relations is calculated through the attention mechanism. For the contribution of the possible subject, finally combine the relationship pre-classification results to weight the enhanced semantics of each relationship to find the enhanced semantics of the possible subject, and send the enhanced semantics combined with the possible subject to the object and relationship extraction module. Complete the final relation triplet extraction. The experimental results show that, compared with the baseline model, the CasAug model proposed in this paper has improved the effect of relation extraction, and CasAug's ability to deal with overlapping problems and extract multiple relations is also better than the baseline model, indicating that the semantic enhancement mechanism proposed in this paper It can further reduce the judgment of redundant relations and alleviate the problem of triple overlap.
AbstractList Relational extraction is one of the basic tasks related to information extraction in natural language processing, and is an important link and core task in the fields of information extraction, natural language understanding, and information retrieval. None of the existing relation extraction methods can effectively solve the problem of triple overlap. The CasAug model proposed in this paper based on the CasRel framework combined with the semantic enhancement mechanism can solve this problem to a certain extent. The CasAug model enhances the semantics of the identified possible subjects by adding a semantic enhancement mechanism, First, based on the semantic coding of possible subjects, pre-classify the possible subjects, and then combine the subject lexicon to calculate the semantic similarity to obtain the similar vocabulary of possible subjects. According to the similar vocabulary obtained, each word in different relations is calculated through the attention mechanism. For the contribution of the possible subject, finally combine the relationship pre-classification results to weight the enhanced semantics of each relationship to find the enhanced semantics of the possible subject, and send the enhanced semantics combined with the possible subject to the object and relationship extraction module. Complete the final relation triplet extraction. The experimental results show that, compared with the baseline model, the CasAug model proposed in this paper has improved the effect of relation extraction, and CasAug's ability to deal with overlapping problems and extract multiple relations is also better than the baseline model, indicating that the semantic enhancement mechanism proposed in this paper It can further reduce the judgment of redundant relations and alleviate the problem of triple overlap.
Author Guan, Zeli
Liu, PeiYu
Du, JunPing
Shao, YingXia
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SubjectTerms Attention mechanism
Complex systems
Data mining
Encoding
Natural language processing
Relation extraction
Semantic enhancement
Semantic similarity
Semantics
Subject lexicon
Task analysis
Vocabulary
Title Relation Extraction Model Based on Semantic Enhancement Mechanism
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