Discourse connectives are known to be subject to both usage and sense ambiguity, as has already been discussed in the literature. But discourse connectives are no different from other linguistic expressions in being subject to other types of ambiguity as well. Four are illustrated and discussed here.

Full text discourse parsing relies on texts comprehensively annotated with discourse relations. To this end, we address a significant gap in the inter-sentential discourse relations annotated in the Penn Discourse Treebank (PDTB), namely the class of cross-paragraph implicit relations, which account for 30% of inter-sentential relations in the corpus. We present our annotation study to explore the incidence rate of adjacent vs. non-adjacent implicit relations in cross-paragraph contexts, and the relative degree of difficulty in annotating them. Our experiments show a high incidence of non-adjacent relations that are difficult to annotate reliably, suggesting the practicality of backing off from their annotation to reduce noise for corpus-based studies. Our resulting guidelines follow the PDTB adjacency constraint for implicits while employing an underspecified representation of non-adjacent implicits, and yield 62% inter-annotator agreement on this task.

The PDTB Annotator is a tool for annotating and adjudicating discourse relations based on the annotation framework of the Penn Discourse TreeBank (PDTB). This demo describes the benefits of using the PDTB Annotator, gives an overview of the PDTB Framework and discusses the tool’s features, setup requirements and how it can also be used for adjudication.

We present the second version of the Penn Discourse Treebank, PDTB-2.0, describing its lexically-grounded annotations of discourse relations and their two abstract object arguments over the 1 million word Wall Street Journal corpus. We describe all aspects of the annotation, including (a) the argument structure of discourse relations, (b) the sense annotation of the relations, and (c) the attribution of discourse relations and each of their arguments. We list the differences between PDTB-1.0 and PDTB-2.0. We present representative statistics for several aspects of the annotation in the corpus.

This paper presents a corpus study of parenthetical constructions in two different corpora: the Penn Discourse Treebank (PDTB, (PDTBGroup, 2008)) and the RST Discourse Treebank (Carlson et al., 2001). The motivation for the study is to gain a better understanding of the rhetorical properties of parentheticals in order to enable a natural language generation system to produce parentheticals as part of a rhetorically well-formed output. We argue that there is a correlation between syntactic and rhetorical types of parentheticals and establish two main categories: ELABORATION/EXPANSION-type NP-modifier parentheticals and NON-ELABORATION/EXPANSION-type VP- or S-modifier parentheticals. We show several strategies for extracting these from the two corpora and discuss how the seemingly contradictory results obtained can be reconciled in light of the rhetorical and syntactic properties of parentheticals as well as the decisions taken in the annotation guidelines.