Fully Parsing the Penn Treebank

Proceedings of the Human Language Technology Conference of the North American Chapter of the ACL, pages 184–191, New York, June 2006. c⃝2006 Association for Computational Linguistics Fully Parsing the Penn Treebank� Ryan Gabbard Mitchell Marcus Department of Computer and Information Science University of Pennsylvania {gabbard,mitch}@cis.upenn.edu Seth Kulick Institute for Research in Cognitive Science University of Pennsylvania skulick@cis.upenn.edu Abstract We present a two stage parser that recov- ers Penn Treebank style syntactic analy- ses of new sentences including skeletal syntactic structure, and, for the first time, both function tags and empty categories. The accuracy of the first-stage parser on the standard Parseval metric matches that of the (Collins, 2003) parser on which it is based, despite the data fragmentation caused by the greatly enriched space of possible node labels. This first stage si- multaneously achieves near state-of-the- art performance on recovering function tags with minimal modifications to the un- derlying parser, modifying less than ten lines of code. The second stage achieves state-of-the-art performance on the recov- ery of empty categories by combining a linguistically-informed architecture and a rich feature set with the power of modern machine learning methods. 1 Introduction The trees in the Penn Treebank (Bies et al., 1995) are annotated with a great deal of information to make various aspects of the predicate-argument structure easy to decode, including both function tags and markers of “empty” categories that represent dis- placed constituents. Modern statistical parsers such as (Collins, 2003) and (Charniak, 2000) however ig- nore much of this information and return only an �We would like to thank Fernando Pereira, Dan Bikel, Tony Kroch and Mark Liberman for helpful suggestions. This work was supported in part under the GALE program of the Defense Advanced Research Projects Agency, Contract No. HR0011- 06-C-0022, and in part by the National Science Foundation un- der grants NSF IIS-0520798 and NSF EIA 02-05448 and under an NSF graduate fellowship. impoverished version of the trees. While there has been some work in the last few years on enrich- ing the output of state-of-the-art parsers that output Penn Treebank-style trees with function tags (e.g. (Blaheta, 2003)) or empty categories (e.g. (Johnson, 2002; Dienes and Dubey, 2003a; Dienes and Dubey, 2003b), only one system currently available, the de- pendency graph parser of (Jijkoun and de Rijke, 2004), recovers some representation of both these aspects of the Treebank representation; its output, however, cannot be inverted to recover the original tree structures. We present here a parser,1 the first we know of, that recovers full Penn Treebank-style trees. This parser uses a minimal modification of the Collins parser to recover function tags, and then uses this enriched output to achieve or better state-of-the- art performance on recovering empty categories. We focus here on Treebank-style output for two reasons: First, annotators developing additional treebanks in new genres of English that conform to the Treebank II style book (Bies et al., 1995) must currently add these additional annotations by hand, a much more laborious process than correcting parser output (the currently …

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