Triple
T23301682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 法隆寺 |
E590318
|
entity |
| Predicate | 建築的意義 |
P5770
|
FINISHED |
| Object | 古代寺院伽藍配置の典型例 |
—
|
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: 古代寺院伽藍配置の典型例 | Statement: [法隆寺, 建築的意義, 古代寺院伽藍配置の典型例]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 建築的意義 Context triple: [法隆寺, 建築的意義, 古代寺院伽藍配置の典型例]
-
A.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
-
B.
buildings
Indicates that one or more buildings are associated with, located at, or relevant to the referenced entity.
-
C.
architecturalConcept
chosen
Indicates that one entity represents or embodies an architectural concept in relation to another entity.
-
D.
architecturalWork
Indicates that one entity is an architectural creation (such as a building or structure) designed or realized by another entity.
-
E.
architecturalUse
Indicates how a structure, space, or element is intended to be used or function within an architectural context.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196d37fd08190ad2d199c54324c02 |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:04 p.m.