Abstract: The present invention is a system and method for performing semantic analysis that interprets a linguistic structure output by a natural language linguistic analysis system. The semantic analysis system converts the linguistic output by the natural language linguistic analysis system into a data structure model referred to as a semantic discourse representation structure (SemDRS).

Abstract: A computer implemented information retrieval system is provided. The system includes a user input configured to receive a user query relative to the corpus. A machine learning classifier is trained with a first set of training data comprising anchor text relative to at least some of the documents in the corpus. A processing unit is adapted to interact with the classifier to obtain search results relative to the query using the machine learning classifier. In some aspects, the classifier is also trained with a second set of training data. A method of integrating a new document into a corpus of documents is also provided. A method of training a machine learning classifier for retrieving documents from a corpus using two distinct types of training data is also provided.

Abstract: The present invention is a segmenter used in a natural language processing system. The segmenter segments a textual input string into tokens for further natural language processing. In accordance with one feature of the invention, the segmenter includes a tokeinzer engine that proposes segmentations and submits them to a linguistic knowledge component for validation. In accordance with another feature of the invention, the segmentation system includes language specific data that contains a precedence hierarchy for punctuation. If proposed tokens in the input string contain punctuation, they can illustratively be broken into subtokens based on the precedence hierarchy.