2017
EMNLP
EMNLP 2017
SupWSD: A Flexible Toolkit for Supervised Word Sense Disambiguation
Abstract
AbstractIn this demonstration we present SupWSD, a Java API for supervised Word Sense Disambiguation (WSD). This toolkit includes the implementation of a state-of-the-art supervised WSD system, together with a Natural Language Processing pipeline for preprocessing and feature extraction. Our aim is to provide an easy-to-use tool for the research community, designed to be modular, fast and scalable for training and testing on large datasets. The source code of SupWSD is available at http://github.com/SI3P/SupWSD.
🌉
Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
🧭
Keyword Pioneer
— natural language processing pipeline
🐣
Hot Topic Early Bird
— word sense disambiguation
🐝
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, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Classification
Natural Language Processing > Understanding > Named Entity Recognition
Natural Language Processing > Resources & Methods > Text Representation
Machine Learning > Learning Types > Supervised Learning
Natural Language Processing > Applications > Text Processing