Towards Automatic Identification of Discourse Markers in Dialogs: the Case of 'Like'

This article discusses the detection of discourse markers (DM) in dialog transcriptions, by human annotators and by automated means. After a theoretical discussion of the definition of DMs and their relevance to natural language processing, we focus on the role of like as a DM. Results from experiments with human annotators show that detection of DMs is a difficult but reliable task, which requires prosodic information from soundtracks. Then, several types of features are defined for automatic disambiguation of like: collocations, part-of-speech tags and duration-based features. Decision-tree learning shows that for like, nearly 70% precision can be reached, with near 100% recall, mainly using collocation filters. Similar results hold for well, with about 91% precision at 100% recall.

Export Restrictions on Critical Minerals and Metals: Testing the Adequacy of WTO Disciplines

Conventional wisdom on the insufficiency of existing WTO disciplines on export restrictions has triggered momentum on the issue. In this book, Ilaria Espa offers a comprehensive analysis of the scope and coverage of WTO disciplines on export restrictions in light of emerging case law. She investigates whether such rules still provide a credible and effective framework capable of preventing abuses in the use of export restrictive measures on critical minerals and metals during a period of economic crisis and change in international trade patterns. Giving a broad overview of the export restrictions applied to these materials, Espa identifies distinctive features in the proliferation of export barriers and analyses the existing WTO rules to reveal their gaps and inconsistencies. She goes on to present solutions based upon her findings with the aim of bringing more coherence and equity to WTO rules on the export side.