Triple
T6364384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kii Mountains |
E143188
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kōyasan |
E389565
|
NE FINISHED |
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: Kōyasan | Statement: [Kii Mountains, contains, Kōyasan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kōyasan Context triple: [Kii Mountains, contains, Kōyasan]
-
A.
Mount Kōya
chosen
Mount Kōya is a sacred mountainous temple complex in Japan that serves as the spiritual headquarters of Shingon Buddhism and a major pilgrimage destination.
-
B.
Yamatokoriyama
Yamatokoriyama is a Japanese city in Nara Prefecture known for its historic Koriyama Castle and traditional goldfish breeding industry.
-
C.
Koyasan Okunoin
Koyasan Okunoin is one of Japan’s most sacred Buddhist sites, a vast forest cemetery and pilgrimage destination on Mount Koya associated with the revered monk Kobo Daishi.
-
D.
Kumano
Kumano is a coastal city in Japan’s Mie Prefecture known for its scenic Kumano Kodo pilgrimage routes and rugged natural landscapes.
-
E.
Kumano
Kumano was a Mogami-class heavy cruiser of the Imperial Japanese Navy that served during World War II.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008d8c61081908bcaf61510d881ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0680ed0148190b6e310b15b3449ff |
completed | March 22, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c673fe44848190854c36801cc3e5d3 |
completed | March 27, 2026, 12:11 p.m. |
Created at: March 22, 2026, 4:32 p.m.