Triple
T20986518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamanashi Prefecture |
E516903
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Tsuru |
—
|
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: Tsuru | Statement: [Yamanashi Prefecture, hasMunicipality, Tsuru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsuru Context triple: [Yamanashi Prefecture, hasMunicipality, Tsuru]
-
A.
Tsuru
chosen
Tsuru is a small city in Yamanashi Prefecture, Japan, known for its scenic setting near Mount Fuji and its educational institutions.
-
B.
Tsubame
Tsubame is a city in Japan renowned for its high-quality metalworking and cutlery industries.
-
C.
Tsubame
Tsubame is a Japanese Shinkansen train service that operates on the Kyushu Shinkansen line in southern Japan.
-
D.
Murai
Murai is a Japanese surname borne by various notable individuals across fields such as film, music, and sports.
-
E.
Kiku
Kiku was the wife of the Japanese haiku poet Kobayashi Issa, known primarily through references in his life and writings.
- 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fbe31cec8190a1007414148b8abe |
completed | April 21, 2026, 4:24 a.m. |
Created at: April 16, 2026, 1:49 p.m.