Triple
T8340070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leesburg Executive Airport |
E195886
|
entity |
| Predicate | distanceFromWashingtonDCCenter |
P15076
|
FINISHED |
| Object | approximately 33 miles northwest |
—
|
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 33 miles northwest | Statement: [Leesburg Executive Airport, distanceFromWashingtonDCCenter, approximately 33 miles northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromWashingtonDCCenter Context triple: [Leesburg Executive Airport, distanceFromWashingtonDCCenter, approximately 33 miles northwest]
-
A.
distanceToWashingtonDC
chosen
Indicates the physical distance between a given location and Washington, D.C.
-
B.
distanceToWashingtonMonument
Indicates the physical distance between a given entity’s location and the Washington Monument.
-
C.
directionFromWashingtonDC
Indicates the cardinal or relative compass direction of one place or object as measured from Washington, D.C.
-
D.
distanceFromFord’sTheatre
Indicates the spatial distance between an entity and Ford’s Theatre.
-
E.
distanceToSeattle
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd7a3888190b54306ed862aded4 |
completed | March 31, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69cb70c6d0ec8190acf273b0e007b51a |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:57 p.m.