Triple
T26439138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pittsburgh and West Virginia Railway |
E665036
|
entity |
| Predicate | primaryPassengerServiceType |
P175201
|
FINISHED |
| Object | local passenger trains |
—
|
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: local passenger trains | Statement: [Pittsburgh and West Virginia Railway, primaryPassengerServiceType, local passenger trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryPassengerServiceType Context triple: [Pittsburgh and West Virginia Railway, primaryPassengerServiceType, local passenger trains]
-
A.
majorPassengerService
Indicates that a transportation facility or route provides primary or significant passenger service as one of its main functions.
-
B.
hasPassengerServicesType
chosen
Indicates the type or category of passenger services that are provided or associated with an entity.
-
C.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
D.
servesPassengerTrafficType
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
E.
hasPassengerServiceLevel
Indicates the level or quality of passenger service provided in a given transportation context.
- 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_69ee883c851881909e2ab04efbb3c5fe |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: April 26, 2026, 11:56 p.m.