Triple
T22973195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinaloa Cartel |
E571243
|
entity |
| Predicate | controlsTraffickingOf |
P150454
|
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: [Sinaloa Cartel, controlsTraffickingOf, cocaine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlsTraffickingOf Context triple: [Sinaloa Cartel, controlsTraffickingOf, cocaine]
-
A.
controlledTradeWith
Indicates a regulated or restricted trading relationship in which one entity manages, oversees, or limits the trade activities conducted with another entity.
-
B.
prohibitedTradeWith
Indicates that one entity is forbidden or restricted from engaging in trade or commercial exchange with another entity.
-
C.
hasLessStrictTradeControlsThan
Indicates that one entity’s trade regulations or restrictions are more relaxed or permissive compared to those of another entity.
-
D.
hasStricterTradeControlsThan
Indicates that one entity enforces more restrictive or rigorous trade regulations or controls than another entity.
-
E.
regulatesTrafficBetween
Indicates that one entity controls, manages, or directs the flow of traffic occurring between two other entities or locations.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182343a448190a5259cdf721c9d04 |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:48 p.m.