Triple
T13455500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IND/BMT Division |
E311220
|
entity |
| Predicate | hasRollingStockLengthRange |
P16279
|
FINISHED |
| Object | 60-foot to 75-foot cars |
—
|
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: 60-foot to 75-foot cars | Statement: [IND/BMT Division, hasRollingStockLengthRange, 60-foot to 75-foot cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRollingStockLengthRange Context triple: [IND/BMT Division, hasRollingStockLengthRange, 60-foot to 75-foot cars]
-
A.
rollingStockLength
chosen
Indicates the length measurement of a piece of rolling stock in a rail or transit system.
-
B.
usesRollingStockCompatibleWith
Indicates that one entity operates using rolling stock that is technically and operationally compatible with the rolling stock standards or systems associated with another entity.
-
C.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
D.
hasRailWidth
Indicates that one entity has a specified width measurement for its rail or rails.
-
E.
line1RollingStock
Indicates that the rolling stock (e.g., train cars or locomotives) is assigned to or operating on the first line in a multi-line rail system.
- 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.