Work on shallow discourse parsing in English has focused on the Wall Street Journal corpus, the only large-scale dataset for the language in the PDTB framework. However, the data is not openly available, is restricted to the news domain, and is by now 35 years old. In this paper, we present and evaluate a new open-access, multi-genre benchmark for PDTB-style shallow discourse parsing, based on the existing UD English GUM corpus, for which discourse relation annotations in other frameworks already exist. In a series of experiments on cross-domain relation classification, we show that while our dataset is compatible with PDTB, substantial out-of-domain degradation is observed, which can be alleviated by joint training on both datasets.

The Universal Dependencies (UD) project has created an invaluable collection of treebanks with contributions in over 140 languages. However, the UD annotations do not tell the full story. Grammatical constructions that convey meaning through a particular combination of several morphosyntactic elements—for example, interrogative sentences with special markers and/or word orders—are not labeled holistically. We argue for (i) augmenting UD annotations with a ‘UCxn’ annotation layer for such meaning-bearing grammatical constructions, and (ii) approaching this in a typologically informed way so that morphosyntactic strategies can be compared across languages. As a case study, we consider five construction families in ten languages, identifying instances of each construction in UD treebanks through the use of morphosyntactic patterns. In addition to findings regarding these particular constructions, our study yields important insights on methodology for describing and identifying constructions in language-general and language-particular ways, and lays the foundation for future constructional enrichment of UD treebanks.

This work compares two ways of annotating semantic relations expressed in prepositional phrases: semantic classes in the Semantic Network of Adposition and Case Supersenses (SNACS), and tectogrammatical functors from the Prague English Dependency Treebank (PEDT). We compare the label definitions in the respective annotation guidelines to determine expected mappings, then check how well these work empirically using Wall Street Journal text. In the definitions we find substantial overlap in the distributions of the two schemata with respect to participants and circumstantials, but substantial divergence for configurational relationships between nominals. This is borne out by the empirical analysis. Examining the data more closely for participants and circumstantials reveals that there are some unexpected, yet systematic divergences between definitionally aligned groups.