Multilingual normalization of temporal expressions with masked language models

L Lange, J Strötgen, H Adel, D Klakow - arXiv preprint arXiv:2205.10399, 2022 - arxiv.org
The detection and normalization of temporal expressions is an important task and
preprocessing step for many applications. However, prior work on normalization is rule …

A Synergistic Bidirectional LSTM and N-gram Multi-channel CNN Approach Based on BERT and FastText for Arabic Event Identification

N Haffar, M Zrigui - ACM Transactions on Asian and Low-Resource …, 2023 - dl.acm.org
Event extraction from texts continues to pose a challenge for many NLP systems. This article
presents a novel neural network architecture that can extract and classify events from Arabic …

Robust input representations for low-resource information extraction

L Lange - 2022 - publikationen.sulb.uni-saarland.de
Recent advances in the field of natural language processing were achieved with deep
learning models. This led to a wide range of new research questions concerning the stability …

[图书][B] Applying Temporal Information Extraction for Knowledge Management

AA Aljubailan - 2022 - search.proquest.com
The information revolution enabled by the recent breakthroughs in Information and
Communication Technology (ICT) has led to to a radical transformation in the modern …

I still have Time (s): Extending HeidelTime for German Texts

A Lücking, M Stoeckel, G Abrami, A Mehler - arXiv preprint arXiv …, 2022 - arxiv.org
HeidelTime is one of the most widespread and successful tools for detecting temporal
expressions in texts. Since HeidelTime's pattern matching system is based on regular …