Abstract: An intention identification model learning method includes receiving positive data that corresponds to a first skill, generating, based on the positive data that corresponds to the first skill, negative data that corresponds to the first skill, determining a second skill similar to the first skill, obtaining data that corresponds to each second skill, generating a second base model based on the data that corresponds to the second skill and a first base model stored on the server, and performing learning based on the second base model, the positive data, and the negative data that correspond to the first skill, and generating an intention identification model.

Abstract: A semantic parsing method includes extracting, by a first server, a first entity of a first slot from a first user sentence, modifying the first entity to a second entity of a second slot when the first entity is a pronoun, sending a first server request to a second server, and obtaining a first service result from the second server in response to the first service request. The first service request includes indication information of a first intention and the first entity, the second server is an application server that provides a first skill, and the first service result is based on the first intention and the first entity. The first server returns the first service result to a device to output by the device.

Abstract: A semantic parsing method includes extracting, by a first server, a first entity of a first slot from a first user sentence, modifying the first entity to a second entity of a second slot when the first entity is a pronoun, sending a first server request to a second server, and obtaining a first service result from the second server in response to the first service request. The first service request includes indication information of a first intention and the first entity, the second server is an application server that provides a first skill, and the first service result is based on the first intention and the first entity. The first server returns the first service result to a device to output by the device.

Abstract: An intention identification model learning method includes receiving positive data that corresponds to a first skill, generating, based on the positive data that corresponds to the first skill, negative data that corresponds to the first skill, determining, a second skill similar to the first skill, obtaining data that corresponds to each second skill, generating a second base model based on the data that corresponds to the second skill and a first base model stored on the server, and performing learning based on the second base model, the positive data, and the negative data that correspond to the first skill, and generating an intention identification model.