Triple
T12722952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akita Kanto Festival |
E304029
|
entity |
| Predicate | numberOfLanternsOnLargestKanto |
P37175
|
FINISHED |
| Object | about 46 lanterns |
—
|
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: about 46 lanterns | Statement: [Akita Kanto Festival, numberOfLanternsOnLargestKanto, about 46 lanterns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLanternsOnLargestKanto Context triple: [Akita Kanto Festival, numberOfLanternsOnLargestKanto, about 46 lanterns]
-
A.
numberOfShrines
Indicates the total count of shrines associated with a given entity or context.
-
B.
numberOfMainTorii
Indicates the specific count of primary torii gates associated with a given entity.
-
C.
numberOfLights
chosen
Indicates the quantity of lights associated with or present on a given entity.
-
D.
AtsutaShrineIs
Indicates that something has the status, identity, or defining characteristics of Atsuta Shrine.
-
E.
hasDomeLantern
Indicates that one entity possesses or features a dome-shaped lantern structure as part of its form or design.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96403957c81909acdee7bdae71696 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:24 p.m.