Coherence relations can be made linguistically explicit by means of connectives (e.g., but, because) or cue phrases (e.g., on the other hand, which is why), but can also be left implicit and conveyed through the juxtaposition of two clauses or sentences. However, it seems that not all relations are equally easy to reconstruct when they are implicit. In this paper, we explore which features of coherence relations make them more, or less, likely to be conveyed implicitly. We adopt the assumption that expected relations are more often implicit than relations that are not expected, and propose to determine a relation's expectedness using the notion of cognitive complexity. We test our hypotheses by means of a parallel corpus study, in which we analyze the translations of explicit English coherence relations from the Europarl Direct corpus into four target languages: Dutch, German, French, and Spanish. We find that cognitive complexity indeed influences the linguistic marking of coherence relations, and that this does not vary between the languages in our corpus. In addition, we find that a relation's relational and syntactic dependency also influences its linguistic marking, but that these measures are not completely independent of relation type.

In this paper, we show how three often used and seemingly different discourse annotation frameworks – Penn Discourse Treebank (PDTB), Rhetorical Structure Theory (RST), and Segmented Discourse Representation Theory – can be related by using a set of unifying dimensions. These dimensions are taken from the Cognitive approach to Coherence Relations and combined with more fine-grained additional features from the frameworks themselves to yield a posited set of dimensions that can successfully map three frameworks. The resulting interface will allow researchers to find identical or at least closely related relations within sets of annotated corpora, even if they are annotated within different frameworks. Furthermore, we tested our unified dimension (UniDim) approach by comparing PDTB and RST annotations of identical newspaper texts and converting their original end label annotations of relations into the accompanying values per dimension. Subsequently, rates of overlap in the attributed values per dimension were analyzed. Results indicate that the proposed dimensions indeed create an interface that makes existing annotation systems “talk to each other.”

Discourse segmentation is an important step in the process of annotating coherence relations. Ideally, implementing segmentation rules results in text segments that correspond to the units of thought related to each other. This paper demonstrates that accurate segmentation is in part dependent on the propositional content of text fragments, and that completely separating segmentation and annotation does not always yield text segments that correspond to the text units between which a conceptual relationship holds. In addition, it argues that elements belonging to the propositional content of the discourse should necessarily be included in the segmentation, but that inclusion of other text elements, for instance stance markers, should be optional.

Connectives and cue phrases are the most prototypical linguistic elements that signal coherence relations, but by limiting our attention to connectives, we are likely missing out on important other cues readers and listeners use when establishing coherence relations. However, defining the role of other types of linguistic elements in the signaling of coherence relations is not straightforward, and it is also not obvious why and how non-connective elements function as signals for coherence relations. In this paper, we aim to develop a systematic way of categorizing segment-internal elements as signals of coherence relations on the basis of a literature review and evidence from parallel corpora. We propose a three-way distinction between division of labor, agreement, and general collocation to categorize the different ways in which elements inside discourse segments interact with connectives in the marking of coherence relations. In each type of interaction, segment-internal elements can function as signals for coherence relations, but the mechanism behind it is slightly different for each type.

Temporal information is one of the prominent features that determine the coherence in a discourse. That is why we need an adequate way to deal with this type of information during discourse annotation. In this paper, we will argue that temporal order is a relational rather than a segment-specific property, and that it is a cognitively plausible notion: temporal order is expressed in the system of linguistic markers and is relevant in both acquisition and language processing. This means that temporal relations meet the requirements set by the Cognitive approach of Coherence Relations (CCR) to be considered coherence relations, and that CCR would need a way to distinguish temporal relations within its annotation system. We will present merits and drawbacks of different options of reaching this objective and argue in favor of adding temporal order as a new dimension to CCR.