Triple
T17810395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koji Satō |
E444684
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Koji |
—
|
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: Koji | Statement: [Koji Satō, givenName, Koji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koji Context triple: [Koji Satō, givenName, Koji]
-
A.
Koji
chosen
Koji is a Japanese given name commonly associated with notable figures in entertainment, sports, and the arts.
-
B.
Koja
Koja is a coastal district in North Jakarta, Indonesia, known for its dense urban neighborhoods and proximity to the city’s port and industrial areas.
-
C.
Kuo
Kuo is a Wade–Giles romanization of the Chinese surname and name more commonly spelled "Guo" in pinyin.
-
D.
Kogo
Kogo is a settlement located in the Litoral region of Equatorial Guinea.
-
E.
Jinci
Jinci is an ancient temple complex near Taiyuan in Shanxi, China, renowned for its historic architecture, sacred springs, and richly decorated wooden halls.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887a50488190b9c148146ec607e6 |
completed | April 19, 2026, 7:47 a.m. |
Created at: April 10, 2026, 10:14 a.m.