Triple
T25715414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Tokyo |
E644848
|
entity |
| Predicate | approxGreatCircleDistanceMi |
P45616
|
FINISHED |
| Object | 5960 |
—
|
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: 5960 | Statement: [London–Tokyo, approxGreatCircleDistanceMi, 5960]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxGreatCircleDistanceMi Context triple: [London–Tokyo, approxGreatCircleDistanceMi, 5960]
-
A.
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).
-
B.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
-
C.
approximateDistanceKm
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
-
D.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
E.
distanceBetweenHomeCities
Indicates the measured spatial distance separating the home cities of two entities.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 21, 2026, 9:40 p.m.