Triple
T26459716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amtrak Carl Sandburg |
E665594
|
entity |
| Predicate | primaryPassengerMarket |
P99024
|
FINISHED |
| Object | intercity travelers in Illinois |
—
|
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: intercity travelers in Illinois | Statement: [Amtrak Carl Sandburg, primaryPassengerMarket, intercity travelers in Illinois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryPassengerMarket Context triple: [Amtrak Carl Sandburg, primaryPassengerMarket, intercity travelers in Illinois]
-
A.
primaryPassengerGroup
chosen
Indicates the main group of passengers that is most directly associated with or served by a given entity or context.
-
B.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
C.
secondaryPassengerProfile
Indicates that an entity serves as an additional or non-primary passenger associated with a main travel booking or passenger profile.
-
D.
majorPassengerAxis
Indicates that there is a primary route or direction along which the main flow of passengers moves or is organized.
-
E.
passengerSegments
Indicates a relationship where a journey or trip is divided into distinct legs or segments that a passenger travels through.
- 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_69ee883e812c8190a9b5a9cdb87fee5e |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
Created at: April 27, 2026, 12:11 a.m.