Triple
T16301749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shōnai Domain |
E395805
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Tsuruoka |
—
|
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: Tsuruoka | Statement: [Shōnai Domain, administrativeCenter, Tsuruoka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsuruoka Context triple: [Shōnai Domain, administrativeCenter, Tsuruoka]
-
A.
Tsuruoka City
chosen
Tsuruoka City is a coastal city in northern Japan known for its rich culinary culture, historic temples, and designation as a UNESCO Creative City of Gastronomy.
-
B.
Noshiro
Noshiro is a coastal city in northern Japan known for its port on the Sea of Japan and its forestry and basketball traditions.
-
C.
Kōriyama
Kōriyama is a major commercial and transportation hub city located in Japan’s Tōhoku region.
-
D.
Shiraoi
Shiraoi is a coastal town in Hokkaido, Japan, known for its Ainu cultural heritage and natural hot springs.
-
E.
Yonezawa
Yonezawa is a city in southern Yamagata Prefecture, Japan, known for its historic castle town, high-quality Yonezawa beef, and snowy climate.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e32da7081908d8bd320374a5731 |
completed | April 17, 2026, 4:22 p.m. |
Created at: April 10, 2026, 5:06 a.m.