International Business Machines Corporation

Hema Raghavan

Vittorio R Castelli

Radu Florian

Xiaoqiang Luo

Sameer Maskey

A method for automatically extracting and organizing information by a processing device from a plurality of data sources is provided. A natural language processing information extraction pipeline that includes an automatic detection of entities is applied to the data sources. Information about detected entities is identified by analyzing products of the natural language processing pipeline. Identified information is grouped into equivalence classes containing equivalent information. At least one displayable representation of the equivalence classes is created. An order in which the at least one displayable representation is displayed is computed. A combined representation of the equivalence classes that respects the order in which the displayable representation is displayed is produced.

System and method for automatically detecting and interactively displaying information about entities, activities, and events from multiple-modality natural language sources

Creating training data for a natural language processing system may comprise obtaining natural language input, the natural language input annotated with one or more important phrases; and generating training instances comprising a syntactic parse tree of nodes representing elements of the natural language input augmented with the annotated important phrases. In another aspect, a classifier may be trained based on the generated training instances. The classifier may be used to predict one or more potential important phrases in a query.

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Yorktown Heights, NY, United States of America

Hema Raghavan