International Business Machines Corporation

Mitesh Khapra

Ashish Verma

Yedendra Shrinivasan

Noam Slonim

Amrita Saha

Vikas Raykar

Sathish R Indurthi

Mitesh H Vasa

A method comprising using at least one hardware processor for: receiving a topic under consideration (TUC) and a set of claims referring to the TUC; identifying semantic similarity relations between claims of the set of claims; clustering the claims into a plurality of claim clusters based on the identified semantic similarity relations, wherein said claim clusters represent semantically different claims of the set of claims; and generating a list of non-redundant claims comprising said semantically different claims.

Semantic merge of arguments

A cognitive system that automatically assesses subjective answers may be provided. A cognitive engine executing on one or more processors may determine whether a statement parsed from a subjective answer by natural language processing technique is accurate or inaccurate, for each of the plurality of statements based on matching the statement with information associated with a domain of a question from a plurality of data sources, according to an accuracy threshold. An overall assessment of the answer may be automatically determined based on a number of statements determined to be accurate, a number of statements determined to be inaccurate, a number of duplicate statements in the answer relative to a total number of statements in the answer. A visual graphics representing accurate and inaccurate statements may be presented or displayed, allowing a user to interact with the visual graphics to modify the assessment.

Computer-implemented cognitive system for assessing subjective question-answers

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Bengaluru, India

Mitesh Khapra