Triple
T30123653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nquthu |
E765627
|
entity |
| Predicate | nearbyHistoricalBattlefields |
P37770
|
FINISHED |
| Object | Isandlwana |
—
|
NE NERFINISHED |
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: Isandlwana | Statement: [Nquthu, nearbyHistoricalBattlefields, Isandlwana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyHistoricalBattlefields Context triple: [Nquthu, nearbyHistoricalBattlefields, Isandlwana]
-
A.
hasNearbyMilitaryHistorySite
Indicates that an entity is located close to a site of historical military significance, such as a battlefield, fort, or memorial.
-
B.
regionOfBattlesCommemorated
Indicates the geographic region where the battles being commemorated took place.
-
C.
nearbyBattlefield
Indicates that one entity is located close to or in the immediate vicinity of a battlefield.
-
D.
battleSignificanceAtLocation
Indicates the degree of importance or impact that a particular battle has at a specified location.
-
E.
battleOccurredNear
chosen
Indicates that a battle took place in spatial proximity to a specified location or entity.
- 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_69f2247716748190ae4f16998f49ddf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: April 29, 2026, 7:13 p.m.