Triple
T16001718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fine Wind, Clear Morning |
E388108
|
entity |
| Predicate | seriesNumberWithinSet |
P102560
|
FINISHED |
| Object | one of the Thirty-six Views of Mount Fuji |
—
|
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: one of the Thirty-six Views of Mount Fuji | Statement: [Fine Wind, Clear Morning, seriesNumberWithinSet, one of the Thirty-six Views of Mount Fuji]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesNumberWithinSet Context triple: [Fine Wind, Clear Morning, seriesNumberWithinSet, one of the Thirty-six Views of Mount Fuji]
-
A.
hasSeriesNumber
Indicates that an entity is assigned a specific ordinal or sequence number within a series or ordered set.
-
B.
seriesVolumeNumber
Indicates the specific volume number assigned to an item within an ordered series.
-
C.
seriesNumberInCarryOn
Indicates that an item has a specific series or sequence number within a set of carry-on items.
-
D.
seriesNumberOfWorks
chosen
Indicates that an entity is assigned a specific position or sequence number within a series of related works.
-
E.
hasPartOfSeriesPosition
Indicates that an entity occupies a specific position or order within a larger series or sequence.
- 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.