Triple
T13336189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korechika Anami |
E317698
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Anami |
E317698
|
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: Anami | Statement: [Korechika Anami, familyName, Anami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anami Context triple: [Korechika Anami, familyName, Anami]
-
A.
Anami
chosen
Anami is a Japanese surname most notably associated with Korechika Anami, a general in the Imperial Japanese Army during World War II.
-
B.
Yukio
Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
-
C.
Yamanakako
Yamanakako is a village in Yamanashi Prefecture, Japan, known for Lake Yamanaka, one of the Fuji Five Lakes located near Mount Fuji.
-
D.
Ninomiya
Ninomiya is a coastal town in Kanagawa Prefecture, Japan, known for its residential character and proximity to larger Shōnan-area communities.
-
E.
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.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d00b75c8190af98784c7df904c8 |
completed | April 11, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f74612bab88190bf1a895b87be12c1 |
completed | May 3, 2026, 12:56 p.m. |
Created at: April 9, 2026, 9:31 p.m.