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Multilingual Recognition of Temporal Expressions
2020
Recent Advances in Slavonic Natural Languages Processing
The paper presents a multilingual approach to temporal expression recognition (TER) using existing tools and their combination. We observe that the rules based methods perform well on documents using wellformed temporal expressions in a narrower domain (e.g., news), while data driven methods are more stable within less standard language and texts across domains. With combination of the two approaches, we achieved F1 of 0.73 and 0.9 for strict and relaxed evaluations respectively on one English
dblp:conf/raslan/StaryNV20
fatcat:ctgt25yfwnhyzh6phkzubd6d4i