FrameNet Workshop: Developing New NLP Applications

International Computer Science Institute, Berkeley CA

Investigators

Abstract

In recent years, computer systems designed to understand ordinary language have improved rapidly. These advances depend in part on improving the language resources that help systems recognize different senses of individual words and how the parts of a sentence fit together. People understand words largely by relating them to common situations; in 'She tossed the letter across the table to Jerry', one recognizes that the main idea comes from 'toss', and understands the different roles that 'she', 'the letter', 'across the table', and 'to Jerry' play. For the past fifteen years, the FrameNet team at the International Computer Science Institute has been defining situations, called semantic frames, and labeling examples with semantic roles on the constituents of illustrative sentences. The FrameNet knowledge database contains over 1,100 semantic frames, ranging from getting a job to curing a disease, and almost 200,000 labeled sentences. Other researchers have created software to automatically label sentences in open text based on FrameNet data; these automatic semantic role labeling (ASRL) systems facilitate the automatic recognition of events and their participants in documents ranging from news stories and military reports. This award funds a one-week workshop, September 9-13, 2013, introducing FrameNet to a wider range of industry and academic participants. Speakers include the FrameNet team as well as developers and users of ASRL systems. Topics covered range from implications of FrameNet for protecting privacy to using frames in understanding metaphor. Software developers have a hands-on coding session using the new FrameNet library for NLTK; other participants perform hands-on frame definition and annotation.