Event detection

A computer system comprising at least one processor and at least one memory, the at least one memory, individually or collectively, having computer executable instructions stored thereon, which when executed by the at least one processor, enabling the at least one processor to, individually or collectively, implement acts including:

• obtaining a to-be-processed text;
• extracting one or more groups of instance data from the to-be-processed text by using an extraction model, each group of instance data including a first entity instance, a first entity type corresponding to the first entity instance, a second entity instance, a second entity type corresponding to the second entity instance, and a relationship description between the first entity type and the second entity type;
• determining one or more extracted triplets based on the one or more groups of instance data, to obtain an extracted graph, an extracted triplet including the first entity type, the second entity type, and the relationship description between the first entity type and the second entity type in the instance data;
• obtaining graph ontology definition data of one or more candidate events, and obtaining an ontology definition graph corresponding to each candidate event based on the graph ontology definition data, the graph ontology definition data of the one or more candidate events including an entity type used to indicate an entity and a relationship description used to indicate a relationship between entity types;
• determining a similarity between the extracted graph and each ontology definition graph of the one or more candidate events;
• and
• determining an event corresponding to the to-be-processed text from the one or more candidate events based on each similarity.

A non-transitory storage medium having computer executable instructions stored thereon, the computer executable instructions when executed by one or more processors, enabling the one or more processors to, individually or collectively, implement acts comprising:

• obtaining a to-be-processed text;
• extracting one or more groups of instance data from the to-be-processed text by using an extraction model, each group of instance data including a first entity instance, a first entity type corresponding to the first entity instance, a second entity instance, a second entity type corresponding to the second entity instance, and a relationship description between the first entity type and the second entity type;
• determining one or more extracted triplets based on the one or more groups of instance data, to obtain an extracted graph, an extracted triplet including the first entity type, the second entity type, and the relationship description between the first entity type and the second entity type in the instance data;
• obtaining graph ontology definition data of one or more candidate events, and obtaining an ontology definition graph corresponding to each candidate event based on the graph ontology definition data, the graph ontology definition data of the one or more candidate events including an entity type used to indicate an entity and a relationship description used to indicate a relationship between entity types;
• determining a similarity between the extracted graph and each ontology definition graph of the one or more candidate events;
• and
• determining an event corresponding to the to-be-processed text from the one or more candidate events based on each similarity.