Triple
T15955952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoshijirō Umezu |
E386934
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 梅津 美治郎 |
E536834
|
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: 梅津 美治郎 | Statement: [Yoshijirō Umezu, nativeName, 梅津 美治郎]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 梅津 美治郎 Context triple: [Yoshijirō Umezu, nativeName, 梅津 美治郎]
-
A.
梅津 美治郎
梅津美治郎 was a Japanese general who served as the last Chief of the Army General Staff during World War II and played a central role in Japan’s wartime military leadership.
-
B.
梅津美治郎
chosen
梅津美治郎 was a senior Imperial Japanese Army general who served as the last Chief of the Army General Staff during World War II and was later convicted as a Class A war criminal.
-
C.
米内光政
米内光政は、昭和期の日本で海軍大臣や内閣総理大臣を務め、日中戦争・太平洋戦争期の海軍指導者として知られる政治家・海軍軍人である。
-
D.
藤田 嗣治
藤田 嗣治 was a Japanese–French painter and printmaker associated with the École de Paris, renowned for his distinctive milky-white nudes and depictions of cats.
-
E.
伊藤利助
伊藤利助は、日本初代内閣総理大臣として知られる明治時代の政治家・伊藤博文の別名である。
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fb29848190a55cabb49cb19575 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe7c8ef081908fa6da7975c271f6 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:53 a.m.