Triple
T4910184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kasuga Taisha |
E110211
|
entity |
| Predicate | numberOfLanterns |
P37175
|
FINISHED |
| Object | over 3000 |
—
|
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: over 3000 | Statement: [Kasuga Taisha, numberOfLanterns, over 3000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLanterns Context triple: [Kasuga Taisha, numberOfLanterns, over 3000]
-
A.
numberOfLights
chosen
Indicates the quantity of lights associated with or present on a given entity.
-
B.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern associated with another entity.
-
C.
hasDomeLantern
Indicates that one entity possesses or features a dome-shaped lantern structure as part of its form or design.
-
D.
numberOfChandeliers
Indicates the quantity of chandeliers associated with a given entity or context.
-
E.
hasNumberOfShamashLights
Indicates the relationship specifying how many Shamash (helper) lights are present or associated with an object or setting.
- 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.