Triple
T14580786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Series E6 Shinkansen |
E342185
|
entity |
| Predicate | maximumSpeedOnAkitaShinkansen |
P2096
|
FINISHED |
| Object | 130 km/h |
—
|
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: 130 km/h | Statement: [Series E6 Shinkansen, maximumSpeedOnAkitaShinkansen, 130 km/h]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumSpeedOnAkitaShinkansen Context triple: [Series E6 Shinkansen, maximumSpeedOnAkitaShinkansen, 130 km/h]
-
A.
miniShinkansenPrecededBy
Indicates that one mini Shinkansen service, line, or project occurs or is implemented after and in sequence to another specified mini Shinkansen service, line, or project.
-
B.
maxSpeed
chosen
Indicates the greatest possible speed at which an entity can move or operate under specified conditions.
-
C.
travelTimeFromTokyoByShinkansen
Indicates the amount of time required to travel from Tokyo to another location using the Shinkansen (bullet train).
-
D.
hasShinkansenStop
Indicates that a location is served by and includes a stop for a Shinkansen (high-speed rail) line.
-
E.
maximumSpeedRecord
Indicates that an entity holds the highest recorded speed value (a speed record) within a given context or category.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb41e71748190a1deacc819dd26d3 |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.