Triple
T4204843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saigyō |
E86157
|
entity |
| Predicate | hasCanonization |
P54357
|
FINISHED |
| Object | classical Japanese poet |
—
|
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: classical Japanese poet | Statement: [Saigyō, hasCanonization, classical Japanese poet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonization Context triple: [Saigyō, hasCanonization, classical Japanese poet]
-
A.
hasPartInCanonization
Indicates that an entity participated in or contributed to the process of canonization of another entity.
-
B.
helpedCanonize
Indicates that one entity contributed to or facilitated the process by which another entity was officially recognized as a canon or canonized figure.
-
C.
canonizedAs
Indicates that an authority, typically a religious institution, has formally declared someone to be a saint or holy figure.
-
D.
canonized
Indicates that a religious authority has formally declared someone to be a saint or worthy of official veneration.
-
E.
hasClosedCanon
Indicates that a body of authoritative texts is considered complete and no additional works can be added to it.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0382eafc8190946bf45bf28095dd |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af02e4e2308190b527e3b78eb8fa71 |
completed | March 9, 2026, 5:27 p.m. |
Created at: March 9, 2026, 3:49 p.m.