Abstract: A text containing a word is received by a computing device. The word is compared to inventory words in a sense inventory. The sense inventory comprises at least one inventory word and at least one concept corresponding to the at least one inventory word. Upon matching the word to an inventory word in the sense inventory, a concept for the word is identified by comparing each concept related to the inventory word to the word. The concept is assigned the word.

Abstract: The present disclosure provides methods and systems for performing syntactic analysis of a text. In some implementations the method includes performing rough syntactic analysis of the text, generating a graph of generalized constituents of the text and filtering arcs of the graph of generalized constituents with a combination classifier which includes a tree classifier and one or more linear classifiers. The combination classifier is trained using parallel analysis of an untagged two-language text corpus.

Abstract: The present disclosure provides methods and systems for performing syntactic analysis of a text. In some implementations the method includes performing rough syntactic analysis of the text, generating a graph of generalized constituents of the text and filtering arcs of the graph of generalized constituents with a combination classifier which includes a tree classifier and one or more linear classifiers. The combination classifier is trained using parallel analysis of an untagged two-language text corpus.

Abstract: A first text in a first language is received by a computing device. At least one unknown word in the first text in the first language is detected. At least one second language is selected. For each second language, a first set of texts in the first language and a second set of texts in the second language are received. The first set of texts in the first language is aligned with the second set of texts in the second language. The unknown word is mapped to at least one word in the second set of texts aligned with the at least one unknown word, and a semantic class corresponding to the at least one aligned word is identified. The semantic class is assigned to the at least one unknown word.

Abstract: An unknown word is received by a computing device. A plurality of potential semantic classes to assign to the unknown word are determined using a processor. A classifier for the unknown word using a text corpora is built using the processor. Based at least in part on the built classifier, the unknown word is classified with at least one semantic class from the plurality of potential semantic classes. The unknown word is added to a semantic hierarchy as an instance of the at least one semantic class.

Abstract: A text containing a word is received by a computing device. The word is compared to inventory words in a sense inventory. The sense inventory comprises at least one inventory word and at least one concept corresponding to the at least one inventory word. Upon matching the word to an inventory word in the sense inventory, a concept for the word is identified by comparing each concept related to the inventory word to the word. The concept is assigned the word.