Triple
T21677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Dulles International Airport |
E430
|
entity |
| Predicate | hasPeopleMover |
P941
|
FINISHED |
| Object | mobile lounge system |
—
|
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: mobile lounge system | Statement: [Washington Dulles International Airport, hasPeopleMover, mobile lounge system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPeopleMover Context triple: [Washington Dulles International Airport, hasPeopleMover, mobile lounge system]
-
A.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
-
B.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
C.
hasStreetcarSystem
Indicates that a place possesses or is served by an operational streetcar (tram) transit system.
-
D.
hasTransportationSystem
chosen
Indicates that an entity possesses, operates, or is served by an organized system for transporting people or goods.
-
E.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
- 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.