Construction of Chinese Open Domain Event Graph Integrating Sentiment Semantics and Syntactic Structure
In the construction process of large-scale open domain event graph,lack of annotation data and unknown event types cause difficulties in the transfer of limited domain event graph construction method.To solve this problem,we utilize rule matching methods to efficiently identify multiple event logical relationships contained in open domain texts,and integrate sentiment semantics and syntactic structure information analysis to improve the accuracy of event extraction,in order to better complete the task of constructing event graphs.Firstly,we summarize and expand various logical relationship extraction templates such as cause and effect,succession,condition,transition,etc.,and screen logical relationship event sentences based on rule templates and dependency parsing information.Secondly,we innovatively introduce the sentiment semantic analysis method to accurately identify event types by capturing the sentiment semantics of events and inter-event relations on the basis of syntactic structural information,and then extract event arguments.Then,the semantic similarity is computed for event fusion,and the<preceding event,event logical relation,subsequent event>ternary is constructed to get the event graph,and further event generalization is performed to construct the abstract event graph.Finally,taking the"2022 Mpox Incident"event data as the data source,empirical analysis proves that the open domain event graph construction method can realize the identification of different types of events and reveal the logical relationships between events.Its effectiveness and feasibility are verified.The construction of the Chinese open domain event graph not only fills the gaps in the existing theories of event graph construction,but also provides powerful data support for decision-making and event development prediction.
Open DomainEvent GraphDependency ParsingSemantic Dependency ParsingSentiment Analysis