Triple
T24702536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R62A subway car |
E611789
|
entity |
| Predicate | designedForGauge |
P128239
|
FINISHED |
| Object | standard gauge |
—
|
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: standard gauge | Statement: [R62A subway car, designedForGauge, standard gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedForGauge Context triple: [R62A subway car, designedForGauge, standard gauge]
-
A.
gaugeCompatibleWith
chosen
Indicates that one gauge can be properly used with, mounted to, or function correctly in conjunction with another specified component or system.
-
B.
gaugeType
Indicates the specific kind or category of gauge associated with an entity or measurement.
-
C.
gaugeGroup
Indicates a relationship where a physical or theoretical model is associated with the gauge group that defines its underlying symmetry structure.
-
D.
gaugeFactor
Indicates a proportional conversion or scaling relationship between two quantities, specifying how one value changes relative to another.
-
E.
designedToMeasure
Indicates that one entity was intentionally created or configured for the purpose of quantifying, assessing, or evaluating another entity or its properties.
- 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_69e2c4d76d148190b58ad612467149a5 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 3:23 a.m.