Triple
T17737786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsukiyomi Shrine |
E442768
|
entity |
| Predicate | dedicatedTo |
P500
|
FINISHED |
| Object | Tsukuyomi |
—
|
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: Tsukuyomi | Statement: [Tsukiyomi Shrine, dedicatedTo, Tsukuyomi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsukuyomi Context triple: [Tsukiyomi Shrine, dedicatedTo, Tsukuyomi]
-
A.
Tsukuyomi
chosen
Tsukuyomi is the moon god in Shinto mythology, known as one of the principal deities born from the creator god Izanagi.
-
B.
Tamotsu Takama
Tamotsu Takama was a Japanese naval officer known for commanding the aircraft carrier Hiryū during World War II.
-
C.
Kagutsuchi
Kagutsuchi is the Shinto god of fire whose birth fatally burned his mother Izanami and led to significant events in Japanese mythology.
-
D.
Omi Hakkei
Omi Hakkei is a celebrated series of scenic landscape views in Japan’s Ōmi Province that has inspired numerous artworks and literary references.
-
E.
Samaru
Samaru is a prominent university town and research hub near Zaria in Kaduna State, Nigeria, best known for hosting the main campus of Ahmadu Bello University.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47aca27448190943c75e723ceefcc |
completed | April 19, 2026, 6:48 a.m. |
Created at: April 10, 2026, 10:09 a.m.