Triple
T19357618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sachio Kinugasa |
E484190
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kinugasa |
—
|
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: Kinugasa | Statement: [Sachio Kinugasa, familyName, Kinugasa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinugasa Context triple: [Sachio Kinugasa, familyName, Kinugasa]
-
A.
Kinugasa
chosen
Kinugasa is a small genus of flowering plants in the family Melanthiaceae, known for its distinctive ornamental species native to East Asia.
-
B.
Nichigei
Nichigei is the commonly used abbreviated name for the Nihon University College of Art, a prominent art and design faculty in Japan.
-
C.
Gembu
Gembu is a town located on the Mambilla Plateau in Taraba State, eastern Nigeria, known for its cool climate and scenic highland landscapes.
-
D.
Nuriro
Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
-
E.
Koshun
Koshun is a music producer known for working on projects associated with the artist Amala.
- 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e619096c1081909ce2cbf7ae804e73 |
completed | April 20, 2026, 12:16 p.m. |
Created at: April 10, 2026, 1:34 p.m.