Language processing apparatus, language processing method, and computer program

A language processing method wherein the sample of the dependency structure of the input sentence is generated from the probability model defined by the segment unit model parameter and the sentence unit model parameter and the suitable dependency structure is determined from the generated sample by using a maximum spanning tree searching method.

A language processing method wherein the label of the modification relation as well as a destination of modification of each word in the input sentence are simultaneously processed by a segment unit model and a sentence unit model by generating a sample of labeled dependency structure tree of the input sentence by using a segment unit model parameter with label information and a sentence unit model parameter with label information.

A language processing method wherein the label of the modification relation and the destination of modification are simultaneously processed in the sentence unit model in the input sentence while the destination of modification and the label are separately processed in the segment unit model in the input sentence by generating the sample of the labeled dependency structure tree of the input sentence by using a segment unit model parameter without label information, the model parameter for labeling and the sentence unit model parameter with label information.

A language processing apparatus comprising:

• a dynamic sample generating part that generates the sample of the dependency structure of the input sentence from the probability model defined by the segment unit model parameter and the sentence unit model parameter;
• and
• a solution searching part that determines the suitable dependency structure from the generated sample by using a maximum spanning tree searching method.

A language processing apparatus comprising:

• a labeled dynamic sample generating part that processes the label of the modification relation as well as a destination of modification of each word in the input sentence simultaneously by a segment unit model and a sentence unit model by generating a sample of labeled dependency structure tree of the input sentence by using a segment unit model parameter with label information and a sentence unit model parameter with label information;
• and
• a solution searching part that determines the suitable dependency structure from the generated sample by using a maximum spanning tree searching method.

A language processing apparatus comprising:

• a labeled dynamic sample generating part that processes the label of the modification relation and the destination of modification simultaneously in the sentence unit model in the input sentence and processes the destination of modification and the label separately in the segment unit model in the input sentence by generating the sample of the labeled dependency structure tree of the input sentence by using a segment unit model parameter without label information, the model parameter for labeling and the sentence unit model parameter with label information;
• and
• a solution searching part that determines the suitable dependency structure from the generated sample by using a maximum spanning tree searching method.