Triple
T18416645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Horikawa |
E441909
|
entity |
| Predicate | eraName |
P2938
|
FINISHED |
| Object | Jōtoku |
—
|
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: Jōtoku | Statement: [Emperor Horikawa, eraName, Jōtoku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jōtoku Context triple: [Emperor Horikawa, eraName, Jōtoku]
-
A.
Jōtoku
chosen
Jōtoku was a Japanese era (nengō) of the late 11th century, notable as part of the Heian period court chronology.
-
B.
Daisaku
Daisaku is a Japanese given name most notably borne by Daisaku Ikeda, the Buddhist philosopher, educator, and longtime president of the Soka Gakkai movement.
-
C.
Nishiarai Daishi
Nishiarai Daishi is a prominent Buddhist temple in Tokyo, Japan, known as a major pilgrimage site dedicated to warding off misfortune and bringing good luck.
-
D.
Gyōda
Gyōda is a city in Saitama Prefecture, Japan, known for its historic Oshi Castle and well-preserved traditional townscape.
-
E.
Kotoku Sato
Kotoku Sato was a Japanese lieutenant general in World War II who led the 31st Division during the Burma Campaign, including the ill-fated offensive toward Kohima in India.
- 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a284b608190b77c360a72aceb7a |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 10:47 a.m.