International Business Machines Corporation

Chenguang Wang

Yunyao Li

Anbang Xu

Huaiyu Zhu

Laura Chiticariu

Alan Akbik

Sanjana Sahayaraj

Honglei Zhuang

Victor K Ondego

A computer-implemented method according to one embodiment includes identifying features of a plurality of data instances within a target domain; assigning weights to the plurality of data instances within the target domain, based on similarities among the features; selecting a subset of the plurality of data instances within the target domain, based on the weights; associating expert annotations with respective ones of data instances within the subset; and training a machine learning algorithm, utilizing the subset of the plurality of data instances and associated expert annotations.

Implementing a domain adaptive semantic role labeler

Methods, systems, and computer program products for a semi-automatic process for creating a natural language processing resource are provided herein. A computer-implemented method includes identifying multiple annotation tasks in connection with natural language processing of input text, and automatically determining, based on analysis of (i) parameters related to the identified annotation tasks and (ii) parameters related to annotation task users, routing instructions for the identified annotation tasks, wherein the routing instructions comprise (a) instructions to route a first sub-set of the identified annotation tasks to non-expert annotation task users and (b) instructions to route a second sub-set of the identified annotation tasks to expert annotation task users. The method also includes routing, in accordance with the routing instructions, the first sub-set of the identified annotation tasks to the non-expert annotation task users and the second sub-set of the identified annotation tasks to the expert annotation task users.

Semi-automatic process for creating a natural language processing resource

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Fremont, CA, United States of America

Chenguang Wang