Triple
T36194655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Division (New York City Subway) |
E1047087
|
entity |
| Predicate | hasPlatformLengthStandard |
P127328
|
FINISHED |
| Object | IRT-standard platform length |
—
|
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: IRT-standard platform length | Statement: [A Division (New York City Subway), hasPlatformLengthStandard, IRT-standard platform length]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlatformLengthStandard Context triple: [A Division (New York City Subway), hasPlatformLengthStandard, IRT-standard platform length]
-
A.
hasStandardStraightLength
Indicates that an entity has a specified standard length measured along a straight line.
-
B.
platformLength
chosen
Indicates that one entity specifies the physical length or extent of a platform associated with another entity.
-
C.
maximumStandardLength
Indicates the greatest allowable or specified length for something according to a defined standard.
-
D.
hasVeryLongPlatform
Indicates that an entity possesses a platform whose length is significantly greater than typical or standard platforms.
-
E.
hasLowerBarLength
Indicates that one entity’s bar length is shorter than the bar length of another entity.
- 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_69f76e3d4fbc81908c159c7beeb4ce00 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: May 3, 2026, 4:08 p.m.