Triple
T58630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida Islands |
E1160
|
entity |
| Predicate | distanceToHoniaraApprox |
P3350
|
FINISHED |
| Object | about 30–40 kilometers |
—
|
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 30–40 kilometers | Statement: [Florida Islands, distanceToHoniaraApprox, about 30–40 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToHoniaraApprox Context triple: [Florida Islands, distanceToHoniaraApprox, about 30–40 kilometers]
-
A.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
B.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
C.
peakRouteMileage
Indicates the maximum total distance covered by a particular route over a specified period or under peak operating conditions.
-
D.
distanceFromBoston
Indicates the spatial distance between a given entity’s location and the city of Boston.
-
E.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24c9057348190aa6692eeeae19569 |
completed | Feb. 28, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69a24ac7547c81909bb68f327cdb9158 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24c8fa20c8190aacc38e53d1f654c |
completed | Feb. 28, 2026, 2:01 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.