this paper we refer to the specific subtask of participant role identification as predicate argument tagging. The type of syntactic and semantic information associated with verbs in Levin's Preliminary Classification of English verbs, [Levin,93] can be a useful resource for an automatic predicate argument tagging system. For instance, the 'meet' class includes the following members, meet, consult, debate and visit, which can all be used to refer to the meeting event type described above. In addition, the following types of syntactic frames are associated with these verbs: A met/visited/debated/consulted B A met/visited/debated/consulted with B

With growing interest in Chinese Language Processing, numerous NLP tools (e.g., word segmenters, part-of-speech taggers, and parsers) for Chinese have been developed all over the world. However, since no large-scale bracketed corpora are available to the public, these tools are trained on corpora with different segmentation criteria, part-of-speech tagsets and bracketing guidelines, and therefore, comparisons are difficult. As a first step towards addressing this issue, we have been preparing a large bracketed corpus since late 1998. The first two installments of the corpus, 250 thousand words of data, fully segmented, POS-tagged and syntactically bracketed, have been released to the public via LDC (www.ldc.upenn.edu). In this paper, we discuss several Chinese linguistic issues and their implications for our treebank-ing efforts and how we address these issues when developing our annotation guidelines. We also describe our engineering strategies to improve speed while ensuring annotation quality. 1

, we describe how the Penn Discourse Tree-Bank (PDTB) can serve as a valuable large scale annotated corpus resource for furthering research in NLG and for inducing models for the development of NLG systems. The PDTB is annotated for discourse relations, and encodes explicitly the elements

The current study presents a conversion and unification of the Penn Discourse TreeBank 2.0 under the XML format. The converted corpus allows for a simultaneous search for syntactically specified discourse information on the basis of the XQuery standard.

This paper describes our approach to the development of a Proposition Bank, which involves the addition of semantic information to the Penn English Treebank. Our primary goal is the labeling of syntactic nodes with specific argument labels that preserve the similarity of roles such as the window

The Penn Discourse Treebank (PDTB) was released to the public in 2008. It remains the largest manually annotated corpus of discourse relations to date. Its focus on discourse relations that are either lexically grounded in explicit discourse connectives or associated with sentential adjacency has

The performance of PCFGs estimated from tree banks is shown to be sensitive to the particular way in which linguistic constructions are represented as trees in the tree bank. This paper presents a theoretical analysis of the effect of different tree representations for PP attachment on PCFG

Discourse TreeBank (PDTB) provides annotations of the argument structure, attribution and semantics of discourse connectives. In this paper, we provide the rationale of the tagset, detailed descriptions of the senses with corpus examples, simple semantic definitions of each type of sense tags as well

reentrancies from f-structures generated automatically for the Penn-II treebank trees and use them in an LDD resolution algorithm to parse new text. Unlike (Collins, 1999; Johnson, 2002), in our approach resolution of LDDs is done at f-structure (attribute-value structure representations of basic predicate

This paper describes a new, large scale discourse-level annotation project -- the Penn Discourse TreeBank (PDTB). We present an approach to annotating a level of discourse structure that is based on identifying discourse connectives and their arguments. The PDTB is being built directly on top