Table 2 Data splits to train and test each model (listed in the header)
From: Hybrid natural language processing tool for semantic annotation of medical texts in Spanish
| Â | UMLS entities, temporal entities, miscellaneous entities, temporality/experiencer attributes | Medication information | Negation/speculation | |||
|---|---|---|---|---|---|---|
| Â | #Texts | #Tokens | #Texts | #Tokens | #Texts | #Tokens |
Train | 720 | 175203 | 720 | 175203 | 7739 | 693271 |
Train (CC) | 820 | 205011 | 1085 | 285876 | 7839 | 723079 |
Dev | 240 | 58670 | 240 | 58670 | 240 | 58670 |
Test | 240 | 58300 | 240 | 58300 | 240 | 58300 |
Test (HE) | 200 | 27332 | 200 | 27332 | 200 | 27332 |