Triple
T11053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronald Reagan Washington National Airport |
E224
|
entity |
| Predicate | distanceFromDowntown |
P1299
|
FINISHED |
| Object | approximately 3 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 3 miles | Statement: [Ronald Reagan Washington National Airport, distanceFromDowntown, approximately 3 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDowntown Context triple: [Ronald Reagan Washington National Airport, distanceFromDowntown, approximately 3 miles]
-
A.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
B.
partOfMetropolitanArea
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
-
C.
hasMajorHighway
Indicates that a location or area is served by or directly connected to a major highway route.
-
D.
hasMainStreet
Indicates that a place or locality possesses a primary street commonly recognized as its main thoroughfare.
-
E.
hasBorough
Indicates that one entity is located within, belongs to, or is administratively part of a specific borough.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242cd8fb481909562f114f4ce7700 |
completed | Feb. 28, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69a23fe6b0bc8190bcce9b74f2c5fb08 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a242cce40481908e5eae0c94313c25 |
completed | Feb. 28, 2026, 1:20 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.