Triple
T16736182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangor and Aroostook Railroad |
E406723
|
entity |
| Predicate | hadPassengerService |
P4906
|
FINISHED |
| Object | yes (historically, limited) |
—
|
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: yes (historically, limited) | Statement: [Bangor and Aroostook Railroad, hadPassengerService, yes (historically, limited)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPassengerService Context triple: [Bangor and Aroostook Railroad, hadPassengerService, yes (historically, limited)]
-
A.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
-
B.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
C.
hadOnboardService
Indicates that an onboard service was provided or available during a particular trip, journey, or transport event.
-
D.
isInPassengerService
Indicates that an entity (such as a vehicle, vessel, or aircraft) is currently being used to carry passengers as part of regular service.
-
E.
formerPassengerService
chosen
Indicates that an entity previously provided passenger transportation services but no longer does so.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c3a86848190a03f243dd1bdb899 |
completed | April 18, 2026, 2:59 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.