Raytheon Bbn Technologies Corp.

Other

Ramp Holdings, Inc.

Ralph Mark Weischedel

Jinxi Xu

Scott Richard Miller

Elizabeth Megan Boschee

Marjorie Ruth Freedman

Libin Shen

Alex Baron

Lance Arthur Ramshaw

Heidi Jennifer Fox

Michael R Kayser

The invention relates to cross-document entity co-reference systems in which naturally occurring entity mentions in a document corpus are analyzed and transformed into name clusters that represent global entities. In a first aspect of the invention, a name variation module analyzes naturally occurring names of entities extracted from the document corpus and provides an initial set of equivalent names that could refer to the same real world entity. In a second aspect of the invention, a disambiguation module takes the initial set of equivalent names and uses an agglomerative clustering algorithm to disambiguate the potentially co-referent named entities.

Confidence links between name entities in disparate documents

A method for computer-assisted translation from a source language to a target language makes use of number of rules. Each rule forms an association between a representation of a sequence of source language tokens with a corresponding tree-based structure in the target language. The tree-based structure for each of at least some of the rules represents one or more asymmetrical relations within a number of target tokens associated with the tree-based structure and provides an association of the target tokens with the sequence of source language tokens of the rule. An input sequence of source tokens is decoded according to the rules to generate a representation of one or more output sequences of target language tokens. Decoding includes, for each of at least some sub-sequences of the input sequence of source tokens, determining a tree-based structure associated with the sub-sequence according a match to one of the plurality of rules.

Machine translation

The invention relates to systems and methods for automatically translating documents from a first language to a second language. To carry out the translation of a document, elements of information are extracted from the document and are translated using one or more specialized translation processes. The remainder of the document is separately translated by a statistical translation process. The translated elements of information and the translated remainder are then merged into a final translated document.

Extraction-empowered machine translation

In accordance with methods and systems consistent with the present invention, an improved fact recognition system is provided that automatically learns from syntactic language examples and semantic language examples, thus facilitating development of the system. The language examples are rather simplistic and can be provided by a lay person with little training, thus relieving the need for knowledge engineers. Furthermore, the learning performed by the improved fact recognition system results in a collection of probabilities that is used by the system to recognize facts in a typically more accurate manner than conventional systems.

Fact recognition system

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Canton, MA, United States of America

Ralph Mark Weischedel