Triple
T32110468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerikeri Mission Station |
E820103
|
entity |
| Predicate | hasOldestBuilding |
P18087
|
FINISHED |
| Object | Kemp House |
—
|
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: Kemp House | Statement: [Kerikeri Mission Station, hasOldestBuilding, Kemp House]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOldestBuilding Context triple: [Kerikeri Mission Station, hasOldestBuilding, Kemp House]
-
A.
oldestBuildingDate
Indicates the calendar date on which the earliest or first-constructed building in a given set or area was built or completed.
-
B.
isOldestMuseumIn
Indicates that a museum is the most ancient or earliest established museum within a specified location or region.
-
C.
oldestStandingStructureIn
chosen
Indicates that one entity is the oldest still-existing structure located within the specified place or region.
-
D.
hasCenturyOldArchitecture
Indicates that something features architecture that is at least one hundred years old.
-
E.
isOldestCityIn
Indicates that one city holds the distinction of being the most ancient or earliest established within a specified region, country, or group of cities.
- 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_69f3490209c881908ec0241476715f15 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b967d5308190bbb66d0a8dd52612 |
completed | May 3, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:27 a.m.