Triple
T16315303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania trolley gauge |
E396156
|
entity |
| Predicate | nonStandardGauge |
P122654
|
FINISHED |
| Object | yes |
—
|
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 | Statement: [Pennsylvania trolley gauge, nonStandardGauge, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonStandardGauge Context triple: [Pennsylvania trolley gauge, nonStandardGauge, yes]
-
A.
standardGaugeWidth
Indicates that something has the standard or officially accepted gauge width, typically referring to the distance between two rails in a railway track.
-
B.
gaugeType
Indicates the specific kind or category of gauge associated with an entity or measurement.
-
C.
convertedToStandardGauge
Indicates that something previously using a different gauge has been changed or adapted to conform to a standard gauge specification.
-
D.
primaryGauge
Indicates that one gauge is designated as the main or principal measurement instrument among a set of gauges.
-
E.
standardGaugeWidthComparison
Indicates a comparison between the track gauge width of a railway and the standard gauge width to determine if it is equal to, narrower than, or wider than the standard.
- F. None of above. chosen
Provenance (4 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288de57cc81908cec93309347c385 |
completed | April 17, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69e219fc72c881909d452274e7af8238 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:06 a.m.