Triple
T36108267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karuizawa Prince Hotel |
E1044420
|
entity |
| Predicate | travelTimeFromTokyoByTrain |
P110673
|
FINISHED |
| Object | about 1 hour 10 minutes |
—
|
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 10 minutes | Statement: [Karuizawa Prince Hotel, travelTimeFromTokyoByTrain, about 1 hour 10 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeFromTokyoByTrain Context triple: [Karuizawa Prince Hotel, travelTimeFromTokyoByTrain, about 1 hour 10 minutes]
-
A.
travelTimeFromTokyoByShinkansen
chosen
Indicates the amount of time required to travel from Tokyo to another location using the Shinkansen (bullet train).
-
B.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
C.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
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.
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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:08 p.m.