Triple
T28346641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E8 series Shinkansen |
E717972
|
entity |
| Predicate | gaugeOnStandardShinkansenSections |
P47503
|
FINISHED |
| Object | 1,435 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: 1,435 mm | Statement: [E8 series Shinkansen, gaugeOnStandardShinkansenSections, 1,435 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gaugeOnStandardShinkansenSections Context triple: [E8 series Shinkansen, gaugeOnStandardShinkansenSections, 1,435 mm]
-
A.
operatesShinkansenSection
Indicates that an entity operates or manages the service of a specific section of a Shinkansen (high-speed rail) line.
-
B.
railwayGaugeContext
chosen
Indicates the specific track gauge standard or measurement that applies to, or is used in, a given railway-related context.
-
C.
usesRailGauge
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
D.
hasShinkansenStop
Indicates that a location is served by and includes a stop for a Shinkansen (high-speed rail) line.
-
E.
TokyoMetroSection
Indicates a relationship where a specific segment or portion of the Tokyo Metro railway network is identified as a distinct section within the 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_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64e37f7fc819083809149b6661e3c |
completed | May 2, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 12:43 a.m.