Triple
T13502324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karuizawa resort area |
E320921
|
entity |
| Predicate | travelTimeFromTokyoByShinkansen |
P110673
|
FINISHED |
| Object | about 1 hour |
—
|
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: about 1 hour | Statement: [Karuizawa resort area, travelTimeFromTokyoByShinkansen, about 1 hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeFromTokyoByShinkansen Context triple: [Karuizawa resort area, travelTimeFromTokyoByShinkansen, about 1 hour]
-
A.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
B.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
C.
hasShinkansenStop
Indicates that a location is served by and includes a stop for a Shinkansen (high-speed rail) line.
-
D.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
-
E.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
- F. None of above. chosen
Provenance (4 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf50f4a48190a44fc537b78c32fd |
completed | April 12, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69dbae06061881909a6a6032e0507587 |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:43 p.m.