Triple
T8655523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiroshi Yoshida |
E205404
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Yoshida |
E205404
|
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: Yoshida | Statement: [Hiroshi Yoshida, familyName, Yoshida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoshida Context triple: [Hiroshi Yoshida, familyName, Yoshida]
-
A.
Yoshida
chosen
Yoshida is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and entertainment.
-
B.
Yasuji
Yasuji is a Japanese given name commonly used for males and borne by various notable figures in Japan.
-
C.
Yamada
Yamada is a common Japanese surname borne by many notable figures across fields such as politics, arts, sports, and academia.
-
D.
Yamakita
Yamakita is a rural town in Kanagawa Prefecture, Japan, known for its mountainous terrain, hot springs, and access to outdoor activities such as hiking and river sports.
-
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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4844586081909b687e278496eefa |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32a1e1de88190a98ce4b6aea1a148 |
completed | April 6, 2026, 3:35 a.m. |
Created at: March 30, 2026, 6:29 p.m.