Triple
T21936040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fubuki class |
E541689
|
entity |
| Predicate | classificationByJapan |
P133352
|
FINISHED |
| Object | Special Type (Tokugata) |
—
|
LITERAL 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: Special Type (Tokugata) | Statement: [Fubuki class, classificationByJapan, Special Type (Tokugata)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classificationByJapan Context triple: [Fubuki class, classificationByJapan, Special Type (Tokugata)]
-
A.
legalClassificationInJapan
Indicates how something is categorized or defined under Japanese law.
-
B.
JapaneseDesignation
chosen
Indicates that one entity is formally designated, named, or classified in the Japanese language or by a Japanese authority.
-
C.
rankByCommonnessInJapan
Indicates how items are ordered based on how commonly they occur or are found in Japan.
-
D.
JapaneseTermType
Indicates the classification of a Japanese term according to its linguistic type or usage category (e.g., part of speech, form, or function).
-
E.
regionOfJapan
Indicates that one entity is a geographic region that is part of, or located within, Japan.
- F. None of above.
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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124048fe48190987340d5a6945176 |
completed | April 28, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:53 p.m.