Triple
T22603066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Someiyoshino |
E574880
|
entity |
| Predicate | statusInJapan |
P148898
|
FINISHED |
| Object | most widely planted cherry cultivar |
—
|
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: most widely planted cherry cultivar | Statement: [Someiyoshino, statusInJapan, most widely planted cherry cultivar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusInJapan Context triple: [Someiyoshino, statusInJapan, most widely planted cherry cultivar]
-
A.
statusInYomi
Indicates the role, rank, or condition an entity holds within the realm or context of Yomi.
-
B.
statusInIndonesia
Indicates the legal, social, or operational standing or condition of an entity specifically within the context of Indonesia.
-
C.
Sekisui-inStatus
Indicates the current operational or functional status associated with Sekisui-in.
-
D.
statusInUnitedStates
Indicates the legal or official standing that an entity holds within the jurisdiction of the United States.
-
E.
statusInThailand
Indicates the legal, social, or official standing or condition an entity holds specifically within the context of Thailand.
- F. None of above. chosen
Provenance (4 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1626eb178819096866d03a78f82fc |
completed | April 29, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 2:51 p.m.