Triple
T23391947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokote, Akita |
E594041
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Yurihonjo, Akita |
—
|
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: Yurihonjo, Akita | Statement: [Yokote, Akita, borderedBy, Yurihonjo, Akita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yurihonjo, Akita Context triple: [Yokote, Akita, borderedBy, Yurihonjo, Akita]
-
A.
Yokote, Akita
Yokote, Akita is a city in Akita Prefecture, Japan, known for its heavy snowfall and the traditional Yokote Kamakura Snow Festival featuring igloo-like snow huts.
-
B.
Higashinaruse, Akita
Higashinaruse, Akita is a small mountainous village in Akita Prefecture, Japan, known for its heavy snowfall, natural scenery, and traditional rural lifestyle.
-
C.
Yurihonjō
chosen
Yurihonjō is a coastal city in Akita Prefecture, Japan, known for its rice farming, sake production, and scenic Sea of Japan shoreline.
-
D.
Daisen, Akita
Daisen, Akita is a city in Akita Prefecture, Japan, known for hosting the nationally famous Omagari fireworks competitions.
-
E.
Kuroishi, Aomori
Kuroishi, Aomori is a small city in Aomori Prefecture, Japan, known for its traditional hot spring areas, historic streets, and cultural festivals.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a49ca5a0819091b74ca59e7fedd4 |
completed | April 29, 2026, 6:26 a.m. |
Created at: April 17, 2026, 5:36 p.m.