Triple
T5002378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 摺鉢山 |
E112402
|
entity |
| Predicate | 文化的影響 |
P2008
|
FINISHED |
| Object | 多くの戦争映画やドキュメンタリーに登場する |
—
|
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: 多くの戦争映画やドキュメンタリーに登場する | Statement: [摺鉢山, 文化的影響, 多くの戦争映画やドキュメンタリーに登場する]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 文化的影響 Context triple: [摺鉢山, 文化的影響, 多くの戦争映画やドキュメンタリーに登場する]
-
A.
culturalSphere
Indicates that one entity belongs to, is influenced by, or participates in the cultural domain, tradition, or milieu defined by another entity.
-
B.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
C.
hasCulturalImpact
chosen
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
D.
culturalLayer
Indicates the relationship in which something belongs to, originates from, or is associated with a particular cultural stratum, tradition, or level within a culture.
-
E.
culturalMovement
Indicates that an entity is associated with, participates in, or belongs to a particular cultural movement or trend.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.