Triple
T20328459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiroki Kuroda |
E492403
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hiroki |
—
|
NE NERFINISHED |
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: Hiroki | Statement: [Hiroki Kuroda, givenName, Hiroki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hiroki Context triple: [Hiroki Kuroda, givenName, Hiroki]
-
A.
Hiroki
chosen
Hiroki is a Japanese given name commonly used for males, often associated with meanings like "vast," "great," or "abundant joy" depending on the kanji used.
-
B.
Hiroto
Hiroto is a masculine Japanese given name commonly associated with meanings like “large,” “great,” or “ocean,” depending on the kanji used.
-
C.
Hiroshi
Hiroshi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as art, politics, and entertainment.
-
D.
Hiroaki
Hiroaki is a Japanese masculine given name that can be written with various kanji combinations and is borne by numerous notable figures in fields such as politics, sports, and the arts.
-
E.
Hiroyuki
Hiroyuki is a Japanese given name commonly used for men, associated with various notable figures in entertainment, technology, and other fields.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677e637e48190b5582e97fe1000c0 |
completed | April 20, 2026, 7 p.m. |
Created at: April 16, 2026, 11:22 a.m.