Abstract: The technical solutions relate to the fields of artificial intelligence technologies and natural language processing technologies. According to an embodiment, entity detection is performed on a query text to acquire a target entity; a feature representation of the query text is generated by using a pre-trained context representation model; and based on the feature representation of the query text and pre-acquired feature representations of entity categories corresponding to the target entity, the target entity is linked to an entity category with the highest matching degree.

Abstract: A method and device for correcting an error in a text are provided. The method includes: preprocessing the text to obtain at least one segment of the text; generating a plurality of candidate segments for the segment; scoring the plurality of candidate segments with a tree model, to obtain respective first scoring results of the plurality of candidate segments; scoring the plurality of candidate segments with a deep neural network model, to obtain respective second scoring results of the plurality of candidate segments; for each candidate segment, calculating a scoring of the candidate segment based on the first scoring result and the second scoring result of the candidate segment; ranking the plurality of candidate segments according to the scorings of the candidate segments, to obtain a ranking result; and correcting the error in the text according to the ranking result.

Abstract: A method and device for correcting an error in a text are provided. The method includes: preprocessing the text to obtain at least one segment of the text; generating a plurality of candidate segments for the segment; scoring the plurality of candidate segments with a tree model, to obtain respective first scoring results of the plurality of candidate segments; scoring the plurality of candidate segments with a deep neural network model, to obtain respective second scoring results of the plurality of candidate segments; for each candidate segment, calculating a scoring of the candidate segment based on the first scoring result and the second scoring result of the candidate segment; ranking the plurality of candidate segments according to the scorings of the candidate segments, to obtain a ranking result; and correcting the error in the text according to the ranking result.