Triple
T19054339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayama |
E466351
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Miura |
—
|
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: Miura | Statement: [Hayama, neighboringMunicipality, Miura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miura Context triple: [Hayama, neighboringMunicipality, Miura]
-
A.
Miura
chosen
Miura is a coastal city on the Miura Peninsula in Kanagawa Prefecture, Japan, known for its fishing industry, beaches, and scenic ocean views.
-
B.
Shimamoto
Shimamoto is a town in Osaka Prefecture, Japan, located between Kyoto and Osaka along the Yodo River.
-
C.
Katsuura
Katsuura is a coastal city in Chiba Prefecture, Japan, known for its fishing port, seafood markets, and scenic Pacific shoreline.
-
D.
Moriya
Moriya is a city in Ibaraki Prefecture, Japan, known as a suburban residential and commuter hub within the Greater Tokyo area.
-
E.
Shima Sakon
Shima Sakon was a renowned samurai commander of the late Sengoku period, best known for serving Ishida Mitsunari and fighting bravely against Tokugawa forces at the Battle of Sekigahara.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc049f64819093ae9fda26a49bd2 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 10, 2026, 12:03 p.m.