Triple
T16001758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hokusai Manga |
E388109
|
entity |
| Predicate | approximateNumberOfImages |
P116339
|
FINISHED |
| Object | 4000 |
—
|
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: 4000 | Statement: [Hokusai Manga, approximateNumberOfImages, 4000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfImages Context triple: [Hokusai Manga, approximateNumberOfImages, 4000]
-
A.
numberOfImagesReturned
Indicates the total count of images that are produced or provided as the result of a query, request, or operation.
-
B.
numberOfImagesTaken
Indicates the quantity of images that have been captured or recorded in relation to a given subject or event.
-
C.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
-
D.
approximateNumberOfDrawings
chosen
Indicates an estimated or rough count of drawings associated with an entity.
-
E.
numberOfStills
Indicates the quantity of still images associated with or contained in a given entity or context.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142dc081c819082527e3fa8773460 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:55 a.m.