Triple
T2371094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Activase |
E46090
|
entity |
| Predicate | treatsPathophysiologicProcess |
P4714
|
FINISHED |
| Object | thrombus formation |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: thrombus formation | Statement: [Activase, treatsPathophysiologicProcess, thrombus formation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsPathophysiologicProcess Context triple: [Activase, treatsPathophysiologicProcess, thrombus formation]
-
A.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
B.
treatsAnatomicalSite
Indicates that an action, intervention, or agent is directed toward and intended to treat a specific anatomical site.
-
C.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
D.
treatment
chosen
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
E.
pathologyFeature
Indicates that one entity is a pathological characteristic, sign, or abnormal finding associated with another entity in a medical or biological context.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc771302481908540e31abb5aeeba |
completed | March 7, 2026, 6:36 a.m. |
| PD | Predicate disambiguation | batch_69abc59b88348190a2d6c08f69974117 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:56 p.m.