Triple
T16120757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 秦野市 |
E391130
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Yamakita |
—
|
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: Yamakita | Statement: [秦野市, borderedBy, Yamakita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yamakita Context triple: [秦野市, borderedBy, Yamakita]
-
A.
Yamakita
chosen
Yamakita is a rural town in Kanagawa Prefecture, Japan, known for its mountainous terrain, hot springs, and access to outdoor activities such as hiking and river sports.
-
B.
Yamaga
Yamaga is a historic city in Japan known for its traditional lantern festival and hot spring resorts in northern Kumamoto Prefecture.
-
C.
Yamakoshi
Yamakoshi is a recurring character from the Disney XD sitcom "Pair of Kings," known as a mystical fish with prophetic abilities and a quirky, comedic presence.
-
D.
Yamakawa
Yamakawa is a Japanese surname historically associated with notable Meiji-era figures, including the influential educator and social reformer Ōyama Sutematsu.
-
E.
Yasuji
Yasuji is a Japanese given name commonly used for males and borne by various notable figures in Japan.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20200acac8190a47e6a917ff8dd34 |
completed | April 17, 2026, 9:48 a.m. |
Created at: April 10, 2026, 5 a.m.