TEI2GO: A Multilingual Approach for Fast Temporal Expression Identification

arXiv:2403.16804v1 Announce Type: new
Abstract: Temporal expression identification is crucial for understanding texts written in natural language. Although highly effective systems such as HeidelTime exist, their limited runtime performance hampers adoption in large-scale applications and production environments. In this paper, we introduce the TEI2GO models, matching HeidelTime's effectiveness but with significantly improved runtime, supporting six languages, and achieving state-of-the-art results in four of them. To train the TEI2GO models, we used a combination of manually annotated reference corpus and developed …

abstract adoption applications arxiv cs.cl environments identification language multilingual natural natural language paper performance production production environments scale systems temporal type understanding