Triple
T5088168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanganyika |
E114687
|
entity |
| Predicate | hasEthnicTensionsBetween |
P55763
|
FINISHED |
| Object | Twa and Luba communities |
—
|
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: Twa and Luba communities | Statement: [Tanganyika, hasEthnicTensionsBetween, Twa and Luba communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnicTensionsBetween Context triple: [Tanganyika, hasEthnicTensionsBetween, Twa and Luba communities]
-
A.
hasEthnicTensionHistory
chosen
Indicates that there has been a history of conflict, strain, or hostility between ethnic groups within the referenced context.
-
B.
diplomaticTensionBetween
Indicates a strained or conflict-prone diplomatic relationship existing between two entities.
-
C.
geographicRivalry
Indicates a competitive or adversarial relationship between entities that arises from their geographic proximity, territorial interests, or spatial influence.
-
D.
conflictOrCooperationWith
Indicates the presence, nature, or degree of either conflict or cooperation between two entities.
-
E.
religiousConflictBetween
Indicates a relationship where two entities are in opposition or dispute due to differing religious beliefs, practices, or affiliations.
- 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.