Triple
T21679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Dulles International Airport |
E430
|
entity |
| Predicate | distanceFrom |
P1299
|
FINISHED |
| Object | approximately 26 miles west of downtown Washington, D.C. |
—
|
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 26 miles west of downtown Washington, D.C. | Statement: [Washington Dulles International Airport, distanceFrom, approximately 26 miles west of downtown Washington, D.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFrom Context triple: [Washington Dulles International Airport, distanceFrom, approximately 26 miles west of downtown Washington, D.C.]
-
A.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
B.
distanceFromBoston
Indicates the spatial distance between a given entity’s location and the city of Boston.
-
C.
near
Indicates that one entity is located at a short distance from another entity in space or position.
-
D.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
-
E.
locatedAcrossRiverFrom
Indicates that one entity is situated on the opposite side of a river relative to another entity.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24654724481909ba14b7f68d2a472 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.