Triple
T1556820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kono |
E33223
|
entity |
| Predicate | notableBearer |
P458
|
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: [Kono, notableBearer, Taro Kono]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taro Kono Context triple: [Kono, notableBearer, 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.
Jirō Minami
Jirō Minami was a Japanese general and colonial administrator who served as Governor-General of Korea during the later period of Japanese rule.
-
C.
Koji Sato
Koji Sato is a Japanese automotive executive who serves as the president and CEO of Toyota Motor Corporation.
-
D.
Takeo Kanade
Takeo Kanade is a pioneering Japanese computer scientist and roboticist renowned for his foundational contributions to computer vision, robotics, and autonomous systems.
-
E.
Kiyohide Shima
Kiyohide Shima was an Imperial Japanese Navy admiral during World War II who led a cruiser-destroyer force in major Pacific engagements.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908704d208190937af41c6454df4e |
completed | March 5, 2026, 4:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3b2c2788190a22c3b45dedb1484 |
completed | March 8, 2026, 10:09 p.m. |
Created at: March 4, 2026, 7:27 p.m.