Triple
T5088178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanganyika |
E114687
|
entity |
| Predicate | hasUNOperationType |
P54028
|
FINISHED |
| Object | peacekeeping |
—
|
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: peacekeeping | Statement: [Tanganyika, hasUNOperationType, peacekeeping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUNOperationType Context triple: [Tanganyika, hasUNOperationType, peacekeeping]
-
A.
hasOperationType
Indicates the specific kind or category of operation associated with an entity or process.
-
B.
hasGlobalOperationsIn
Indicates that an entity conducts business or operational activities across multiple countries within the specified region or location.
-
C.
hasBusinessOperation
Indicates that one entity conducts, manages, or is engaged in a commercial or organizational activity involving another entity.
-
D.
hasTaskType
Indicates that an entity is associated with or classified under a specific type or category of task.
-
E.
hasUNMandateType
chosen
Indicates the specific type or category of United Nations mandate under which an action, mission, or operation is authorized or conducted.
- 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_69bd443e941881908eb4e8c685b6f656 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75219a94819094fc54c1df448470 |
completed | March 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69bd7159adc881909effd4382c395c66 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:40 p.m.