← Back to papers
2019 NAACL NAACL 2019

The DISRPT 2019 Shared Task on Elementary Discourse Unit Segmentation and Connective Detection

Abstract

AbstractIn 2019, we organized the first iteration of a shared task dedicated to the underlying units used in discourse parsing across formalisms: the DISRPT Shared Task on Elementary Discourse Unit Segmentation and Connective Detection. In this paper we review the data included in the task, which cover 2.6 million manually annotated tokens from 15 datasets in 10 languages, survey and compare submitted systems and report on system performance on each task for both annotated and plain-tokenized versions of the data.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Amir Zeldes , Debopam Das , Erick Galani Maziero , Juliano Antonio , Mikel Iruskieta

Topics

Natural Language Processing > Understanding > Syntax Natural Language Processing > Applications > Information Extraction

Keywords

syntactic parsing discourse parsing text segmentation elementary discourse unit connective detection
Download PDF

Related papers

Semantic Spatial Representation: a unique representation of an environment based on an ontology for robotic applications 2019
SPARSE: Structured Prediction using Argument-Relative Structured Encoding 2019
Learning Multilingual Word Embeddings Using Image-Text Data 2019
Correlation Coefficients and Semantic Textual Similarity 2019
An Adversarial Learning Framework For A Persona-Based Multi-Turn Dialogue Model 2019