Triple
T4910200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kasuga Taisha |
E110211
|
entity |
| Predicate | mainHallStyle |
P14461
|
FINISHED |
| Object | Kasuga-zukuri honden |
—
|
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: Kasuga-zukuri honden | Statement: [Kasuga Taisha, mainHallStyle, Kasuga-zukuri honden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainHallStyle Context triple: [Kasuga Taisha, mainHallStyle, Kasuga-zukuri honden]
-
A.
hasMainHallType
chosen
Indicates the specific category or kind of main hall associated with an entity.
-
B.
hasMainHall
Indicates that an entity possesses or includes a primary or central hall as a significant internal space.
-
C.
buildingStyleOfChamber
Indicates the architectural style or design type associated with a particular chamber.
-
D.
mainChamber
Indicates that something is the primary or central chamber or room within a larger structure or system.
-
E.
architecturalStyle
Indicates the architectural design tradition, movement, or style that characterizes the form and appearance of a structure or built work.
- 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_69bd44132b94819088522d92beaadc78 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e99414081908c3d3283f563bba4 |
completed | March 20, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69bd6c325e188190823836d79934e9bc |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:29 p.m.