Triple
T12548300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanto Festival |
E300028
|
entity |
| Predicate | numberOfLanternsOnLargestPole |
P37175
|
FINISHED |
| Object | about 46 |
—
|
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 | Statement: [Kanto Festival, numberOfLanternsOnLargestPole, about 46]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLanternsOnLargestPole Context triple: [Kanto Festival, numberOfLanternsOnLargestPole, about 46]
-
A.
numberOfLights
chosen
Indicates the quantity of lights associated with or present on a given entity.
-
B.
numberOfStaircases
Indicates the quantity of distinct staircases associated with or present in a given entity or location.
-
C.
numberOfLaserBeams
Indicates the quantity of laser beams associated with or produced by an entity in a given context.
-
D.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern associated with another entity.
-
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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d95410d0b0819097646edd1b837104 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:58 p.m.