Applying Sentence Simplification to the CoNLL-2008 Shared Task

Our submission to the CoNLL-2008 shared task (Surdeanu et al., 2008) focused on applying a novel method for semantic role labeling to the shared task. Our system first simplifies each sentence to be labeled using a set of hand-constructed rules; the weights of the system are trained on semantic role labeling data to generate simplifications which are as useful as possible for semantic role labeling. Our system is only a semantic role labeling system, and thus did not receive a score for Syntactic Dependencies (or, by extension, a score for the complete problem). Unlike most systems in the shared task, our system took constituency parses as input. On the subtask of semantic dependencies, our system obtained an F1 score of 76.17, the highest in the open task. In this paper we give a high-level overview of the sentence simplification system, and discuss and analyze the modifications to this system required for the CoNLL-2008 shared task. 1 Sentence Simplification The main technical interest of our method is a sentence simplification system. This system is described in depth in (Vickrey and Koller, 2008); for lack of space, we omit many details, including a discussion of related work, from this paper. Current semantic role labeling systems rely primarily on syntactic features in order to identify and classify roles. Features derived from a syntactic parse of the sentence have proven particularly useful (Gildea and Jurafsky, 2002). For example, the syntactic subject of “eat” is nearly always the c © 2008. Licensed under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported license (http://creativecommons.org/licenses/by-nc-sa/3.0/). Some rights reserved. S