Triple
T35804155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 金鯱 |
E1035061
|
entity |
| Predicate | 代表的な設置例 |
P32479
|
FINISHED |
| Object | 名古屋城天守 |
—
|
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: 名古屋城天守 | Statement: [金鯱, 代表的な設置例, 名古屋城天守]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 代表的な設置例 Context triple: [金鯱, 代表的な設置例, 名古屋城天守]
-
A.
notableExampleAt
chosen
Indicates that something serves as a prominent or illustrative example of something else in a particular context or location.
-
B.
registrationOfNotableExample
Indicates that an entity serves as a notable or exemplary instance used to illustrate or document a particular registration.
-
C.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
D.
standardExample
Indicates that something is a typical or canonical instance used to illustrate a general case or concept.
-
E.
notableExampleBy
Indicates that something serves as a prominent or illustrative example provided or created by a particular entity.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a283388c81908e4a9ee3369e8d6f |
completed | May 3, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.