Triple
T36238307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little River |
E891435
|
entity |
| Predicate | distanceToAkaroa |
P204801
|
FINISHED |
| Object | approximately 30 km by road |
—
|
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 30 km by road | Statement: [Little River, distanceToAkaroa, approximately 30 km by road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAkaroa Context triple: [Little River, distanceToAkaroa, approximately 30 km by road]
-
A.
distanceFromKaitaia
Indicates the measured distance between a given location or entity and Kaitaia.
-
B.
distanceToInvercargill
Indicates the measured or calculated distance between a given entity’s location and the city of Invercargill.
-
C.
distanceToWellington
Indicates the measured distance between a given entity’s location and the location of Wellington.
-
D.
distanceToPalmerstonNorth
Indicates the spatial distance between a given location and Palmerston North.
-
E.
distanceToGisborne_km
Indicates the distance, measured in kilometers, from a given place or entity to Gisborne.
- 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_69f76e44993481908fa75e4c48d0aab3 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:09 p.m.