Triple
T32424609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 三井寺 |
E828543
|
entity |
| Predicate | 地域文化への影響 |
P23489
|
FINISHED |
| Object | 大津市の観光と信仰の中心の一つ |
—
|
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: 大津市の観光と信仰の中心の一つ | Statement: [三井寺, 地域文化への影響, 大津市の観光と信仰の中心の一つ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 地域文化への影響 Context triple: [三井寺, 地域文化への影響, 大津市の観光と信仰の中心の一つ]
-
A.
regionOfCulturalImpact
chosen
Indicates the geographic area where an entity’s cultural influence, activities, or effects are most significantly felt or observed.
-
B.
heritageInfluence
Indicates how one entity’s cultural, historical, or ancestral background affects or shapes another entity’s characteristics, behavior, or development.
-
C.
hasCulturalImpact
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
D.
populationUnderCulturalInfluence
Indicates that a population is subject to, shaped by, or significantly affected by a particular cultural influence or set of cultural forces.
-
E.
hasCulturalSignificanceFor
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
- 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_69f3491b28bc8190b75cea7a507f337b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c286ac288190843dac21651babd0 |
completed | May 3, 2026, 3:35 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:54 a.m.