Triple
T22250906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States cocaine trade |
E549973
|
entity |
| Predicate | mainDrug |
P69332
|
FINISHED |
| Object | cocaine |
—
|
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: cocaine | Statement: [United States cocaine trade, mainDrug, cocaine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainDrug Context triple: [United States cocaine trade, mainDrug, cocaine]
-
A.
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.
-
B.
mainDrugRoute
Indicates the primary method or pathway by which a drug is administered or delivered to its target.
-
C.
drugClass
Indicates that one entity is classified as a particular pharmacological or therapeutic category of drugs in relation to another entity.
-
D.
hasDrug
chosen
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
-
E.
drugProduced
Indicates that a particular drug is manufactured or generated by a specified producer or source.
- 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138bd45e88190919660d50c0b94bc |
completed | April 28, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69e72fe1e0cc8190bd13cff2a0846225 |
completed | April 21, 2026, 8:05 a.m. |
Created at: April 16, 2026, 8:39 p.m.