Triple
T6492648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makoto Kobayashi |
E148078
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Makoto Kobayashi |
E148078
|
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: Makoto Kobayashi | Statement: [Makoto Kobayashi, name, Makoto Kobayashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makoto Kobayashi Context triple: [Makoto Kobayashi, name, Makoto Kobayashi]
-
A.
Makoto Kobayashi
chosen
Makoto Kobayashi is a Japanese theoretical physicist renowned for his work on CP violation in the Standard Model, for which he shared the 2008 Nobel Prize in Physics.
-
B.
Makoto Uchida
Makoto Uchida is a Japanese automotive executive who serves as the chief executive officer of Nissan Motor Co.
-
C.
Makoto Yamashita
Makoto Yamashita is a Japanese politician serving as the governor of Nara Prefecture.
-
D.
Senichi Hoshino
Senichi Hoshino was a prominent Japanese baseball manager and former pitcher, best known for revitalizing multiple Nippon Professional Baseball teams and leading them to championship success.
-
E.
Hiro Matsuda
Hiro Matsuda was a renowned Japanese professional wrestler and legendary trainer known for shaping the careers of major stars in the wrestling industry.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a9bf9208190b0957eda06ed3d65 |
completed | March 22, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f470cbce14819099d47d468ae61df7 |
completed | May 1, 2026, 9:22 a.m. |
Created at: March 22, 2026, 4:53 p.m.