timenorm-py
Copyright 2024 Timenorm Python Contributors

This product includes software developed as part of the timenorm project
(https://github.com/clulab/timenorm) by:
  - Steven Bethard
  - Egoitz Laparra
  - Dongfang Xu
  - University of Arizona, Computational Language Understanding Lab (CLU Lab)

Original timenorm is licensed under the Apache License 2.0.

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This Python implementation is based on research and code from:

Laparra, E., Xu, D., & Bethard, S. (2018). From Characters to Time Intervals:
New Paradigms for Evaluation and Neural Parsing of Time Normalizations.
Transactions of the Association for Computational Linguistics, 6, 343-356.

Xu, D., Laparra, E., & Bethard, S. (2019). Pre-trained Contextualized Character
Embeddings Lead to Major Improvements in Time Normalization: A Detailed Analysis.
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics.

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The original timenorm can be found at:
https://github.com/clulab/timenorm

This Python reimplementation maintains API compatibility with the original
SCATE (Semantically Compositional Annotation for TEmporal expressions) component
while providing a pure-Python implementation for easier integration into Python
projects.
