Part-of-speech tagging using latent analogy

摘要

Methods and apparatuses to assign part-of-speech tags to words are described. An input sequence of words is received. A global fabric of a corpus having training sequences of words may be analyzed in a vector space. A global semantic information associated with the input sequence of words may be extracted based on the analyzing. A part-of-speech tag may be assigned to a word of the input sequence based on POS tags from pertinent words in relevant training sequences identified using the global semantic information. The input sequence may be mapped into a vector space. A neighborhood associated with the input sequence may be formed in the vector space wherein the neighborhood represents one or more training sequences that are globally relevant to the input sequence.

主权项

1. A method, comprising:
analyzing a corpus having first training sequences of words in a semantic vector space; extracting a global semantic information associated with an input sequence of words from the semantic vector space; selecting second training sequences of words having part-of-speech tags in the semantic vector space based on the global semantic information and the first training sequences; and assigning a part-of-speech tag to at least one word of the input sequence based on the part-of-speech tags of the second training sequences, wherein at least one of the analyzing, extracting, selecting, and assigning is performed by a processor.