Abstract: A language sequence labeling method and includes: reading a first embedding representation of a language sequence, the first embedding representation including a character-level word embedding representation, a pre-trained word embedding representation, and a global word embedding representation of the language sequence, the global word embedding representation referring to a global context representation of the language sequence; performing first depth transformation (DT) encoding on the first embedding representation based on a first DT recurrent neural network (RNN), to output a first hidden-layer state representation corresponding to each word in the language sequence; and decoding the first hidden-layer state representations of the language sequence, to obtain a labeling result of one or more elements in the language sequence.

Abstract: A language sequence labeling method and includes: reading a first embedding representation of a language sequence, the first embedding representation including a character-level word embedding representation, a pre-trained word embedding representation, and a global word embedding representation of the language sequence, the global word embedding representation referring to a global context representation of the language sequence; performing first depth transformation (DT) encoding on the first embedding representation based on a first DT recurrent neural network (RNN), to output a first hidden-layer state representation corresponding to each word in the language sequence; and decoding the first hidden-layer state representations of the language sequence, to obtain a labeling result of one or more elements in the language sequence.

Abstract: A language processing system according to the present invention includes: an input device 1 that receives an input of an input document; and a unit selecting dictionary 22 that selects a document-information-attached user dictionary that is a user dictionary to which document information is attached. The unit selecting dictionary 22 selects the dictionary, based on the degree of similarity between the input document input from the input unit 1 and the document information attached to the document-information-attached user dictionary. The language processing system further includes a document-information-attached user dictionary storage unit 31 that stores the document-information-attached user dictionary. One or more sentences are attached as the document information to the document-information-attached user dictionary.