SEMI-SUPERVISED PART-OF-SPEECH TAGGING
First Claim
1. A method comprising:
- receiving a text comprising a sequence of words;
selecting a word from the text;
identifying features of the selected word, the features comprising a suffix of the selected word;
applying the features of the selected word to a model to identify probabilities for sets of part-of-speech tags, at least one set of part-of-speech tags comprising at least two part-of-speech tags, each part-of-speech tag representing a part-of-speech;
using the probabilities for sets of part-of-speech tags to weight scores for possible part-of-speech tags for the selected word to form weighted scores;
using the weighted scores to select a part-of-speech tag for the selected word; and
storing the selected part-of-speech tag for the selected word.
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Accused Products
Abstract
A word is selected from a received text and features are identified from the word. The features are applied to a model to identify probabilities for sets of part-of-speech tags. The probabilities for the sets of part-of-speech tags are used to weight scores for possible part-of-speech tags for the selected word to form weighted scores. The weighted scores are used to select a part-of-speech tag for the word and the selected part of speech tag is stored or output. The scores for the possible part-of-speech tags are based on variational approximation parameters trained from a sparse prior over probability distributions describing the probability of a part-of-speech tag given a word.
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Citations
20 Claims
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1. A method comprising:
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receiving a text comprising a sequence of words; selecting a word from the text; identifying features of the selected word, the features comprising a suffix of the selected word; applying the features of the selected word to a model to identify probabilities for sets of part-of-speech tags, at least one set of part-of-speech tags comprising at least two part-of-speech tags, each part-of-speech tag representing a part-of-speech; using the probabilities for sets of part-of-speech tags to weight scores for possible part-of-speech tags for the selected word to form weighted scores; using the weighted scores to select a part-of-speech tag for the selected word; and storing the selected part-of-speech tag for the selected word. - View Dependent Claims (2, 3, 4, 5, 6)
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7. The method of 6 wherein the model is trained by forming partial counts of part-of-speech tags based on a probability of a part-of-speech tag given a set of features.
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8. A computer-readable storage medium having encoded thereon computer-executable instructions causing a processor to execute steps comprising:
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receiving a text comprising a sequence of words; training variational approximation parameters based on a sparse prior distribution of probability distributions that describe the probability of a part-of-speech tag given a word and based on the sequence of words, the variational approximation parameters comprising a separate variational approximation parameter for each occurrence of each word in the sequence of words, each separate variational approximation parameter describing a distribution for a tag given a word; selecting a part-of-speech tag for a word that maximizes a value computed from the distributions formed by the variational approximation parameters; and outputting the selected part-of-speech tag as the part-of-speech tag for the word. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15)
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16. A method comprising:
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receiving a text; selecting a first word in the text; retrieving an entry for the first word from a dictionary stored on a computer-readable storage medium, the entry indicating a set of part-of-speech tags associated with the first word; using the set of part-of-speech tags from the entry to identify a part-of-speech tag for the first word; storing the part-of-speech tag for the first word on a computer-readable storage medium; selecting a second word in the text; determining that the dictionary does not have an entry for the second word; selecting a part-of-speech tag for the second word based in part on probabilities of sets of part-of-speech tags given features of the second word; and storing the part-of-speech tag for the second word on a computer-readable storage medium. - View Dependent Claims (17, 18, 19, 20)
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Specification