Triple
T16824524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haruka Satō |
E408982
|
entity |
| Predicate | hasRomanizedName |
P2508
|
FINISHED |
| Object | Haruka Satou |
—
|
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: Haruka Satou | Statement: [Haruka Satō, hasRomanizedName, Haruka Satou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haruka Satou Context triple: [Haruka Satō, hasRomanizedName, Haruka Satou]
-
A.
Haruka Sato
chosen
Haruka Sato is a Japanese individual whose name is commonly romanized as Haruka Sato.
-
B.
Yui Satō
Yui Satō is a Japanese given name borne by multiple notable individuals, including figures in entertainment and other public fields.
-
C.
Takako Sato
Takako Sato is a Japanese given name bearer, likely a woman of Japanese origin, sharing the common first name Takako and the widespread surname Sato.
-
D.
Yuki Satō
Yuki Satō is a Japanese name shared by multiple notable individuals, including athletes and entertainers, distinguished in their respective fields.
-
E.
Yuka Mizuhara
Yuka Mizuhara is a Japanese-American model and media personality known for her fashion work and for being the younger sister of model-actress Kiko Mizuhara.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b310ffec81908087e5aaacc4a7c2 |
completed | April 18, 2026, 4:36 p.m. |
Created at: April 10, 2026, 5:23 a.m.