Triple
T2371093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Activase |
E46090
|
entity |
| Predicate | affectsBiologicalProcess |
P37860
|
FINISHED |
| Object | fibrinolysis |
—
|
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: fibrinolysis | Statement: [Activase, affectsBiologicalProcess, fibrinolysis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsBiologicalProcess Context triple: [Activase, affectsBiologicalProcess, fibrinolysis]
-
A.
biologicalEvent
Indicates a relationship where an entity participates in, causes, or is affected by a process or occurrence in a biological system.
-
B.
affectsTaxon
Indicates that one entity has an impact or influence on a particular taxon or group of organisms.
-
C.
usedInBiology
Indicates that something is employed, applied, or serves a function within the field or practices of biology.
-
D.
biota
Indicates the presence or composition of living organisms (flora, fauna, or other life forms) associated with a given entity or environment.
-
E.
regulatoryInteraction
Indicates a relationship where one entity modulates, controls, or influences the activity, expression, or function of another entity through regulatory mechanisms.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69abc6443c6c8190b932de2abd8eb28f |
completed | March 7, 2026, 6:31 a.m. |
Created at: March 4, 2026, 7:56 p.m.