Triple
T7668142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 河野太郎 |
E173676
|
entity |
| Predicate | ローマ字表記 |
P2508
|
FINISHED |
| Object | Taro Kono |
E32470
|
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: Taro Kono | Statement: [河野太郎, ローマ字表記, Taro Kono]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taro Kono Context triple: [河野太郎, ローマ字表記, Taro Kono]
-
A.
Taro Kono
chosen
Taro Kono is a prominent Japanese politician and Liberal Democratic Party member known for serving in key cabinet posts such as foreign minister and defense minister and for his reformist, media-savvy profile.
-
B.
Makoto Satō
Makoto Satō is a Japanese actor known for his roles in mid-20th-century cinema and television.
-
C.
Ryoichi Hatayama
Ryoichi Hatayama is a Jaeger pilot in the Pacific Rim universe, known for co-piloting the Mark-6 Jaeger Guardian Bravo against kaiju threats.
-
D.
Takeo
Takeo is a Japanese given name commonly used for males and borne by various notable figures in fields such as politics, business, and the arts.
-
E.
Sakon Yamamoto
Sakon Yamamoto is a Japanese racing driver best known for his stint in Formula One during the mid-2000s with several backmarker teams.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701c26ffc8190894fdef92f877f38 |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc638e62608190958e90b07138a1cc |
completed | April 1, 2026, 12:15 a.m. |
Created at: March 27, 2026, 4 p.m.