Triple
T24569472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akaroa Harbour |
E607893
|
entity |
| Predicate | distanceFromChristchurchByRoad |
P70323
|
FINISHED |
| Object | about 80 km |
—
|
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: about 80 km | Statement: [Akaroa Harbour, distanceFromChristchurchByRoad, about 80 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromChristchurchByRoad Context triple: [Akaroa Harbour, distanceFromChristchurchByRoad, about 80 km]
-
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_69e2c4cc35a48190990b7571bc086df8 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a923635c819097ecac0c82ec5f29 |
completed | April 30, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:28 a.m.