Abstract
We addressed the task to automatically recognize and normalize entities in a French medical corpus. To increase the coverage of our initial French terminology, English terms were translated into French by two different automatic translators. Indexing with a terminology that contained the intersection of the translated terms in combination with several post-processing steps to reduce the number of false-positive detections, gave the best performance results.
| Original language | English |
|---|---|
| Journal | CEUR Workshop Proceedings |
| Volume | 1391 |
| State | Published - 2015 |
| Externally published | Yes |
| Event | 16th Conference and Labs of the Evaluation Forum, CLEF 2015 - Toulouse, France Duration: Sep 8 2015 → Sep 11 2015 |
Keywords
- Concept identification
- Entity recognition
- French terminology
- Term translation
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