Triple
T34409848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auckland–Sydney |
E883225
|
entity |
| Predicate | approximateDistanceMi |
P45616
|
FINISHED |
| Object | 1340 |
—
|
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: 1340 | Statement: [Auckland–Sydney, approximateDistanceMi, 1340]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceMi Context triple: [Auckland–Sydney, approximateDistanceMi, 1340]
-
A.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
-
B.
approximateDistanceFrom
Indicates an estimated or rough measure of how far one entity is from another.
-
C.
approximateGreatCircleDistanceMiles
chosen
Indicates the approximate distance, measured in miles, between two locations along the great-circle path on the surface of a sphere (typically the Earth).
-
D.
approximateDistanceKm
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
-
E.
actualDistanceMi
Indicates the measured physical distance between two entities expressed in miles.
- 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_69f349c1f2208190a09a489bb8b2719d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff1e3e13c08190bb8990c44716b746 |
completed | May 9, 2026, 11:45 a.m. |
| PD | Predicate disambiguation | batch_69ff1dfcaf2c8190aaf2b428d57b7782 |
completed | May 9, 2026, 11:43 a.m. |
Created at: May 1, 2026, 1:59 a.m.