Triple
T11094149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M&GN Joint Railway |
E262331
|
entity |
| Predicate | passengerClosure |
P4906
|
FINISHED |
| Object | 1959 |
—
|
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: 1959 | Statement: [M&GN Joint Railway, passengerClosure, 1959]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerClosure Context triple: [M&GN Joint Railway, passengerClosure, 1959]
-
A.
closedForPassengers
Indicates that a transportation facility or vehicle is not available for use by passengers.
-
B.
passengerAccess
Indicates that a passenger is allowed to enter, use, or move through a particular vehicle, area, or transportation-related facility.
-
C.
formerPassengerService
chosen
Indicates that an entity previously provided passenger transportation services but no longer does so.
-
D.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
E.
passengerConfiguration
Indicates how passengers are arranged, seated, or distributed within a vehicle or transport setting.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a0783e88190aae3d461730c2d70 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d744185a5881909ba4cf151d1798ec |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.