Triple
T26551338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 梅花祭 |
E671684
|
entity |
| Predicate | 関連する象徴 |
P107935
|
FINISHED |
| Object | 梅の香り |
—
|
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: 梅の香り | Statement: [梅花祭, 関連する象徴, 梅の香り]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連する象徴 Context triple: [梅花祭, 関連する象徴, 梅の香り]
-
A.
symbolizes
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
B.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
C.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
D.
symbolismFocus
Indicates that the primary emphasis of a work, element, or representation is on its symbolic meaning rather than its literal or functional aspects.
-
E.
symbolismIn
chosen
Indicates that one entity functions as a symbol or representation within the context, meaning, or interpretive framework of another 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_69eeb32163f08190af5f81282738e27a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f614624c80819084f6febf57f86828 |
completed | May 2, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69f602d7b1b0819095ddd3b5169f8ce2 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 27, 2026, 1:47 a.m.