Triple
T3844982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Kanmu |
E93547
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Yamabe |
E394943
|
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: Yamabe | Statement: [Emperor Kanmu, givenName, Yamabe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yamabe Context triple: [Emperor Kanmu, givenName, Yamabe]
-
A.
Yamabe
chosen
Yamabe was the personal name of Emperor Kanmu, a powerful Japanese emperor of the late 8th and early 9th centuries who moved the capital to Heian-kyō (Kyoto).
-
B.
Yasu
Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
-
C.
Takanami
Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
-
D.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
E.
Fujinami
Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb655c081909ec5ff3d09eb4778 |
completed | March 9, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c788a088190aa91261b83f21d86 |
completed | March 14, 2026, 8:29 a.m. |
Created at: March 9, 2026, 3:18 p.m.