Triple
T26000886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohoka |
E646617
|
entity |
| Predicate | distanceToChristchurchByRoad_km |
P70323
|
FINISHED |
| Object | approximately 25 |
—
|
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: approximately 25 | Statement: [Ohoka, distanceToChristchurchByRoad_km, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToChristchurchByRoad_km Context triple: [Ohoka, distanceToChristchurchByRoad_km, approximately 25]
-
A.
distanceToChristchurch
chosen
Indicates the spatial distance between a given entity’s location and the location of Christchurch.
-
B.
distanceFromQueenstownByRoad
Indicates the road travel distance between a given place and Queenstown.
-
C.
distanceToWellington
Indicates the measured distance between a given entity’s location and the location of Wellington.
-
D.
distanceToTimaru_km
Indicates the physical distance, measured in kilometers, between a given location and Timaru.
-
E.
distanceFromAuckland_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Auckland.
- 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_69e77e89d5848190b54352cdb74f6029 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 22, 2026, 9 a.m.