Triple
T13455517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IND/BMT Division |
E311220
|
entity |
| Predicate | hasMaintenanceYard |
P18851
|
FINISHED |
| Object | various B Division yards in New York City |
—
|
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: various B Division yards in New York City | Statement: [IND/BMT Division, hasMaintenanceYard, various B Division yards in New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaintenanceYard Context triple: [IND/BMT Division, hasMaintenanceYard, various B Division yards in New York City]
-
A.
hasRailYard
chosen
Indicates that one entity possesses, contains, or includes a rail yard as part of its facilities or infrastructure.
-
B.
hasMaintenanceFacilities
Indicates that one entity provides or contains facilities where the other entity can be serviced, repaired, or maintained.
-
C.
hasMaintenance
Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
-
D.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
E.
hasYard
Indicates that one entity possesses or includes a yard as part of its property or premises.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaefc52448190b30d7999f44a9765 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:41 p.m.