Triple
T12355038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 山下 |
E294589
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object | Yamashita |
E361017
|
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: Yamashita | Statement: [山下, romanization, Yamashita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yamashita Context triple: [山下, romanization, Yamashita]
-
A.
Yamashita
chosen
Yamashita is a Japanese surname most famously associated with General Tomoyuki Yamashita, a prominent Imperial Japanese Army commander during World War II.
-
B.
Noboru
Noboru is a Japanese masculine given name commonly borne by notable figures in politics, sports, and entertainment.
-
C.
Yasuhiko
Yasuhiko is a Japanese given name notably borne by Prince Asaka Yasuhiko, a member of the Imperial Family of Japan in the early 20th century.
-
D.
Yamamoto
Yamamoto is a Japanese surname most famously associated with Admiral Isoroku Yamamoto, the commander-in-chief of the Imperial Japanese Navy during World War II.
-
E.
Kiyokawa
Kiyokawa is a small rural village in Kanagawa Prefecture, Japan, known for its mountainous scenery and outdoor recreation.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f8bc60c8190b0ceb84093e70db4 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdee6798c8190b2b47082cf0c32fb |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 8, 2026, 9:54 p.m.