Triple
T37332224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Salerno, Florida |
E926784
|
entity |
| Predicate | distanceToStuartDowntown |
P1299
|
FINISHED |
| Object | approximately 4 miles |
—
|
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 4 miles | Statement: [Port Salerno, Florida, distanceToStuartDowntown, approximately 4 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToStuartDowntown Context triple: [Port Salerno, Florida, distanceToStuartDowntown, approximately 4 miles]
-
A.
distanceToBridgetownCentre
Indicates the measured distance between a given location and the center of Bridgetown.
-
B.
distanceFromGeorgeTown
Indicates the measured spatial distance between a given location and George Town.
-
C.
distanceToKingstonApprox
Indicates an approximate distance between a given location and Kingston.
-
D.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
E.
distanceToKingstown
Indicates the spatial distance between a given location and the place referred to as Kingstown.
- 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.