Triple
T7298288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cocaine |
E167778
|
entity |
| Predicate | affectsNeurotransmitter |
P58407
|
FINISHED |
| Object | dopamine |
—
|
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: dopamine | Statement: [Cocaine, affectsNeurotransmitter, dopamine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsNeurotransmitter Context triple: [Cocaine, affectsNeurotransmitter, dopamine]
-
A.
affectsBiologicalProcess
Indicates a relationship where one entity produces a change or influence on a biological process of another entity or system.
-
B.
hasPharmacologicalEffect
chosen
Indicates that one entity produces a specific pharmacological effect or action on another entity.
-
C.
receptorSystem
Indicates that one entity functions as a receptor system through which another entity receives, processes, or responds to signals or stimuli.
-
D.
isNeuroprotective
Indicates that one entity confers protection to another entity’s nervous system or neural structures, helping to prevent or reduce neural damage or degeneration.
-
E.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8f83c881909e8eae85410f9659 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76e67d88190bd3ca6864f45845a |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3 p.m.