Triple
T15724225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Chōkai |
E381180
|
entity |
| Predicate | isVisibleFrom |
P854
|
FINISHED |
| Object | Yurihonjō |
—
|
NE NERFINISHED |
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: Yurihonjō | Statement: [Mount Chōkai, isVisibleFrom, Yurihonjō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yurihonjō Context triple: [Mount Chōkai, isVisibleFrom, Yurihonjō]
-
A.
Yurihonjō
chosen
Yurihonjō is a coastal city in Akita Prefecture, Japan, known for its rice farming, sake production, and scenic Sea of Japan shoreline.
-
B.
Shiraoi
Shiraoi is a coastal town in Hokkaido, Japan, known for its Ainu cultural heritage and natural hot springs.
-
C.
Higashikawa
Higashikawa is a town in Hokkaido, Japan, known as a gateway to the Daisetsuzan mountain range and for its scenic natural landscapes.
-
D.
Tsuchiura
Tsuchiura is a city in Ibaraki Prefecture, Japan, known for its location on the shores of Lake Kasumigaura and its annual national fireworks competition.
-
E.
Semboku
Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb1fdd4819088f3e243263e5f73 |
completed | April 16, 2026, 2:55 a.m. |
Created at: April 10, 2026, 4:46 a.m.