2018
COLING
COLING 2018
A Flexible and Easy-to-use Semantic Role Labeling Framework for Different Languages
Abstract
AbstractThis paper presents a flexible and open source framework for deep semantic role labeling. We aim at facilitating easy exploration of model structures for multiple languages with different characteristics. It provides flexibility in its model construction in terms of word representation, sequence representation, output modeling, and inference styles and comes with clear output visualization. The framework is available under the Apache 2.0 license.
🌱
Topic Pioneer
— Foundation Models
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Computer Vision
📈
Trend Setter
— Foundation Models
🧭
Keyword Pioneer
— multi-lingual nlp
🐝
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