Triple
T37293874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngāti Pūkenga |
E925745
|
entity |
| Predicate | hasHistoricalIdentity |
P200333
|
FINISHED |
| Object | distinct historical identity |
—
|
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: distinct historical identity | Statement: [Ngāti Pūkenga, hasHistoricalIdentity, distinct historical identity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalIdentity Context triple: [Ngāti Pūkenga, hasHistoricalIdentity, distinct historical identity]
-
A.
hasFormerIdentity
Indicates that an entity previously had a different identity, name, or role before its current one.
-
B.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
-
C.
hasUncertainHistoricIdentity
Indicates that the historic identity of an entity is unclear, disputed, or not definitively established.
-
D.
hasHistoryIn
Indicates that an entity has a past involvement, presence, or record of activity within a particular domain, context, or location.
-
E.
hasHistoricalActor
Indicates that an entity is associated with or involves a specific historical person as a participant or subject.
- 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_69f76eb0f86c819098dee07393e69ec3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff80d9a1d88190a95b1488acd6e2e5 |
completed | May 9, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69ff802ae2dc819093a3cda42b63dcbd |
completed | May 9, 2026, 6:42 p.m. |
| PDg | Predicate description generation | batch_69ff80d8ff208190b9e95d077fd99f78 |
completed | May 9, 2026, 6:45 p.m. |
Created at: May 3, 2026, 4:16 p.m.