Table 1 The description of features with an example that extracted from a biomedical sentence by an entity and relation extraction tool, PKDE4J
From: An application of convolutional neural networks with salient features for relation classification
No | Biomedical features | Description | Example feature record |
|---|---|---|---|
1 | ID | Identifier number of an article | 15248468 |
2 | Sent ID | Sentence id of a sentence | 0 |
| Â | Â | in the abstract of an article | Â |
3 | Entity-L | Entity on the left side | dehydroepiandrosterone sulfate |
4 | Type-L | Type of the entity on the left side | COMPOUND |
5 | Context-L | Context of the entity on the left side | NA; |
6 | Entity-R | Entity on the right side | ubiquinone-9 |
7 | Type-R | Type of the entity on the right side | COMPOUND |
8 | Context-R | Context of the entity on the right side | NA |
9 | Negation | Negativeness of the relation | POSITIVE |
10 | Tense | Tense of the relation | ACTIVE |
11 | Verb | Verb of the relation | increase |
12 | Relation | Reference word of the relation | LOCATION_OF |
13 | Context level | Level of the context in the relation | level=0 |
14 | Verb phrase | Verb phrase | increases hepatic ubiquinone-9 in |
| Â | Â | Â | male F-344 |
15 | Sentence | Raw text of a sentence | Dehydroepiandrosterone sulfate |
| Â | Â | Â | increases hepatic ubiquinone-9 |
| Â | Â | Â | in male F-344 rats |