Triple
T8977861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masaharu Homma |
E214440
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Masaharu |
E191090
|
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: Masaharu | Statement: [Masaharu Homma, givenName, Masaharu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masaharu Context triple: [Masaharu Homma, givenName, Masaharu]
-
A.
Masaharu
chosen
Masaharu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable figures in Japanese history and culture.
-
B.
Harukichi
Harukichi is a Japanese given name most notably borne by Harukichi Hyakutake, an Imperial Japanese Navy admiral during World War II.
-
C.
Toshimichi
Toshimichi is a Japanese given name most famously borne by Ōkubo Toshimichi, a key statesman and leader of the Meiji Restoration.
-
D.
Yoshihisa
Yoshihisa is a Japanese given name commonly used for males.
-
E.
Kenjirō
Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
- 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_69ca839ea8b88190922c6a326ffcc0d3 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc67a33c8481909125acf4b7f0a919 |
completed | April 1, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e3d6191c8190adb41feec1bfa76e |
completed | April 5, 2026, 4:23 a.m. |
Created at: March 30, 2026, 7:02 p.m.