Triple
T4822202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōfuku-ji |
E107735
|
entity |
| Predicate | fiveStoryPagodaHeightMeters |
P18664
|
FINISHED |
| Object | approximately 50 |
—
|
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: approximately 50 | Statement: [Kōfuku-ji, fiveStoryPagodaHeightMeters, approximately 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fiveStoryPagodaHeightMeters Context triple: [Kōfuku-ji, fiveStoryPagodaHeightMeters, approximately 50]
-
A.
hasPagoda
Indicates that one entity possesses, contains, or is characterized by the presence of a pagoda.
-
B.
hasTowerHeight
chosen
Indicates that an entity (such as a tower or structure) has a specific height value associated with it.
-
C.
highestPillarApproximateHeight
Indicates the estimated height value of the tallest pillar in a given context or structure.
-
D.
floorCountOfMinaret
Indicates the number of floors or levels that a minaret has.
-
E.
hasMinaretHeightApprox
Indicates that an entity has a minaret whose height is approximately a specified value, allowing for some margin of imprecision.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.