Triple
T25893755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karasuma Station |
E652404
|
entity |
| Predicate | railGaugeOfLineServed |
P47503
|
FINISHED |
| Object | 1435 mm |
—
|
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: 1435 mm | Statement: [Karasuma Station, railGaugeOfLineServed, 1435 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railGaugeOfLineServed Context triple: [Karasuma Station, railGaugeOfLineServed, 1435 mm]
-
A.
usesRailGauge
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
B.
railwayGaugeContext
chosen
Indicates the specific track gauge standard or measurement that applies to, or is used in, a given railway-related context.
-
C.
railwayTypeServed
Indicates the type of railway system or service that a given entity (such as a station, line, or facility) is designed to serve or accommodate.
-
D.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
E.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced 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_69e7ab3c6cc081908de59bfcc28ec19d |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f603819d188190892465ae5c4ae3cb |
completed | May 2, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 22, 2026, 8:22 a.m.