Triple
T27205332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee |
E683847
|
entity |
| Predicate | primaryActiveCompound |
P6564
|
FINISHED |
| Object | Caffeine |
—
|
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: Caffeine | Statement: [Coffee, primaryActiveCompound, Caffeine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryActiveCompound Context triple: [Coffee, primaryActiveCompound, Caffeine]
-
A.
primaryPsychoactiveComponent
Indicates that one entity is the main psychoactive substance responsible for the primary mind- or behavior-altering effects of another entity.
-
B.
primaryDrug
Indicates that one drug is identified as the main or most important medication in a given treatment, context, or combination relative to other associated drugs.
-
C.
primaryChemicalComponent
chosen
Indicates that one entity is the main or predominant chemical substance composing another entity.
-
D.
primarySubstanceExample
Indicates that one entity serves as the main illustrative example of a particular substance associated with another entity.
-
E.
primaryComponent
Indicates that one entity serves as the main or most important component within another entity or system.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69ff1c91bbac8190b84012dee1cb3b2c |
completed | May 9, 2026, 11:37 a.m. |
| PD | Predicate disambiguation | batch_69ff1c23ca508190bb5a435d765b7e53 |
completed | May 9, 2026, 11:36 a.m. |
Created at: April 27, 2026, 9:37 a.m.