September 17, 2018

12:00 pm / 1:15 pm

Venue

Hackerman B17 @ 3400 N Charles St, Baltimore, MD 21218, USA

Abstract
Analyzing large volumes of text in various languagesand mapping them into a representation that reflects content, rather than form, is one of the great challenges NLP must face. The talk will present UCCA(Universal Conceptual Cognitive Annotation), an approach to structural semantic representation that emphasizes cross-linguistic applicability and accessibility to non-expert annotators, which represents a step towards meeting this challenge. The first part of the talk will introduce theUCCA scheme and show how it provides a typologically motivated characterization of abstract semantic structure. The second part will discuss a transition-based approach to UCCA parsing, and experiments on leveraging annotated data in other formalisms (such as AMR and SDP) to improve UCCA   parsing through multi-task learning. The talk will conclude with an overview of how UCCA is being applied to text-to-text generation tasks, such as machine translation and text simplification, and their evaluation.

All of UCCA’s resources are freely available at http://www.cs.huji.ac.il/~oabend/ucca.html.

Biography

Omri is a faculty member in the Hebrew University’s departments of Computer Science and Cognitive Science. Previously he was a post-doc in Mark Steedman’s lab in the University of Edinburgh. Omri earned his PhD from the Hebrew University of Jerusalem, where he was advised by Ari Rappoport. Before that, he studied mathematics and cognitive sciences in the Hebrew University. Omri’s research focuses on semantics, including semantic representation and parsing, as well as corpus annotation and evaluation. See http://www.cs.huji.ac.il/~oabend/ fordetails.