Abstract: Provided are a man-machine dialogue method and system, computer device and medium. A specific implementation of the method includes: obtaining a current dialogue sentence input by a user; using the current dialogue sentence and a goal type and a goal entity of a preceding dialogue sentence obtained before the current dialogue sentence as an input of a first neural network module of a neural network system, and generating the goal type and the goal entity of the current dialogue sentence by performing feature extraction through the first neural network module; and using the current dialogue sentence, the goal type and the goal entity of the current dialogue sentence and knowledge base data as an input of a second neural network module of the neural network system, and generating a reply sentence by performing feature extraction and classification through the second neural network module.

Abstract: The present disclosure provides a human-computer interaction method and apparatus, computer-readable storage medium and electronic device, and relates to the technical field of computer question answering. The human-computer interaction method includes receiving an input question; extracting entities and relationships involved in the input question; querying an answer to the input question in a knowledge graph according to the entities and the relationships; and displaying a sub-graph of the knowledge graph. The sub-graph of the knowledge graph includes entities involved in the input question and the answer, and a directional identifier, wherein the directional identifier is configured to identify a reasoning path corresponding to the query process.

Abstract: A method for event extraction according to the disclosure includes: processing an object text using a preset extraction model to determine event information of the object text; wherein the event information includes an event element, and an event type and a role corresponding to the event element; and the extraction model includes a classification layer and an output layer; the classification layer is configured to determine a token attribute of a token in the object text; the token attribute includes whether the token is a start token of the event element of any event type and any role, and whether the token is an end token of the event element of any event type and any role; and the output layer is configured to determine the event element according to the token attribute of the token, and determine the event type and the role corresponding to the event element.

Abstract: Provided are a man-machine dialogue method and system, computer device and medium. A specific implementation of the method includes: obtaining a current dialogue sentence input by a user; using the current dialogue sentence and a goal type and a goal entity of a preceding dialogue sentence obtained before the current dialogue sentence as an input of a first neural network module of a neural network system, and generating the goal type and the goal entity of the current dialogue sentence by performing feature extraction through the first neural network module; and using the current dialogue sentence, the goal type and the goal entity of the current dialogue sentence and knowledge base data as an input of a second neural network module of the neural network system, and generating a reply sentence by performing feature extraction and classification through the second neural network module.