Integrating Perspectives on Discourse Annotation (DiscAnn)

Detecting Potentially Under-annotated Explicit Discourse Connectives in the Penn Discourse Treebank (PDTB-3) with LLMs

Theoretical implications of automated discourse parsing in student writing

Comparing human annotations with outputs from generative large language models and examining their alignment with theoretical models of textuality show how computational approaches can shed light on linguistic theories and, vice versa, how linguistic theories can guide the application of computational resources.

Does Linguistic Structure Enrichment Enhance Coherence Assessment? Not With Current Architectures

This work investigates whether enriching text with syntactic and rhetorical information can improve incoherence prediction, and shows that plain texts achieved higher accuracy because the added information was structurally and syntactically incompatible with the language model's architecture.

Cross-Dataset Inconsistencies in Morphological Annotation: Evidence from Universal Dependencies

LLMs as Annotators: Evaluating Model–Human Alignment in Detecting Contentious Language in Historical Corpora

It is suggested that LLMs can serve as auxiliary annotators for sensitive-language detection in historical materials, provided that human oversight and contextual interpretation remain central to annotation workflows.

Semantic labeling with fulfillers in multilingual contexts

This article introduces a novel approach to semantic labeling grounded in the fulfiller concept—a cognitive-semantic theory that highlights the role of absent but contextually inferred elements in meaning construction. We argue that the prevailing semantic labeling practices often neglect this essential aspect of m...