Triple
T1002277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles B. Wheeler Downtown Airport |
E21629
|
entity |
| Predicate | distanceFromDowntownMiles |
P1299
|
FINISHED |
| Object | approximately 1 |
—
|
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 1 | Statement: [Charles B. Wheeler Downtown Airport, distanceFromDowntownMiles, approximately 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDowntownMiles Context triple: [Charles B. Wheeler Downtown Airport, distanceFromDowntownMiles, approximately 1]
-
A.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
B.
distanceFromLosAngeles
Indicates the measured or specified distance between a given entity’s location and the city of Los Angeles.
-
C.
distanceFromSanFrancisco
Indicates the measured distance between a given entity’s location and the city of San Francisco.
-
D.
distanceToLosAngeles
Indicates the measured or calculated distance between a given entity’s location and the city of Los Angeles.
-
E.
isDowntownEndpointOf
Indicates that a location serves as the downtown terminus or endpoint of a route, line, or path.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fcbc04819098d2125518f62ae7 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.