Triple
T10489542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chad–Sudan border |
E247377
|
entity |
| Predicate | hasSmuggling |
P75275
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chad–Sudan border, hasSmuggling, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSmuggling Context triple: [Chad–Sudan border, hasSmuggling, true]
-
A.
hasSmugglingRoutes
chosen
Indicates that an entity maintains or controls secret or illegal transportation paths used to move goods or people covertly.
-
B.
smugglingMethod
Indicates the method or technique used to illegally transport goods or people across borders or through restricted areas.
-
C.
primaryIllegalCommodity
Indicates that the referenced commodity is the main or most significant illegal good involved in an activity, transaction, or case.
-
D.
hasCustomsAndImmigration
Indicates that customs and immigration control services are present or provided at a given location or facility.
-
E.
hasCustomsCheckpoint
Indicates that a location or route includes an official customs inspection point where goods, vehicles, or people are checked for compliance with border regulations.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097ca5c081908b47a08ca7885650 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:23 p.m.