论文信息 - CENTAL at SemEval-2016 Task 12: a linguistically fed CRF model for medical and temporal information extraction

CENTAL at SemEval-2016 Task 12: a linguistically fed CRF model for medical and temporal information extraction

In this paper, we describe the system developed for our participation in the Clinical TempEval task of SemEval 2016 (task 12). Our team focused on the subtasks of span and attribute identification from raw text and proposed a system that integrates both statistical and linguistic approaches. Our system is based on Conditional Random Fields with high-precision linguistic features.

Cédrick Fairon | André Bittar | Patrick Watrin | Damien De Meyere | Charlotte Hansart

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