Triple
T4503870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Passenger Company |
E101284
|
entity |
| Predicate | hasPassengerServiceClass |
P50616
|
FINISHED |
| Object | first class |
—
|
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: first class | Statement: [Federal Passenger Company, hasPassengerServiceClass, first class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerServiceClass Context triple: [Federal Passenger Company, hasPassengerServiceClass, first class]
-
A.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
B.
hasPassengerOnlyService
Indicates that the service provided involves only the transportation of passengers, with no freight or cargo component.
-
C.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
D.
hasBaggageService
Indicates that an entity provides or supports services related to handling, storing, or managing baggage for others.
-
E.
seatClass
chosen
Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56fca7d4819081deb34628e04f00 |
completed | March 20, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69bd521671688190bc655d25fa77eba2 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:01 p.m.