Triple
T17859678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagaoka Station |
E446034
|
entity |
| Predicate | distanceFromTokyoStationOnJoetsuShinkansen |
P69606
|
FINISHED |
| Object | approximately 270 km |
—
|
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: approximately 270 km | Statement: [Nagaoka Station, distanceFromTokyoStationOnJoetsuShinkansen, approximately 270 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTokyoStationOnJoetsuShinkansen Context triple: [Nagaoka Station, distanceFromTokyoStationOnJoetsuShinkansen, approximately 270 km]
-
A.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
B.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
-
C.
distanceFromTokyoStationOnYokosukaLine
chosen
Indicates the distance of a location from Tokyo Station measured specifically along the Yokosuka Line route.
-
D.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
E.
travelTimeFromTokyoByShinkansen
Indicates the amount of time required to travel from Tokyo to another location using the Shinkansen (bullet train).
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4978f34948190a25deb4fd617ad72 |
completed | April 19, 2026, 8:51 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:17 a.m.