Triple
T7368921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shukugawa Park |
E169941
|
entity |
| Predicate | hasSeasonalScenery |
P31151
|
FINISHED |
| Object | spring cherry blossoms |
—
|
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: spring cherry blossoms | Statement: [Shukugawa Park, hasSeasonalScenery, spring cherry blossoms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalScenery Context triple: [Shukugawa Park, hasSeasonalScenery, spring cherry blossoms]
-
A.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
-
B.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
C.
hasSeasonalSpecies
Indicates that certain species are present or occur only during specific seasons in relation to a given context or location.
-
D.
hasSeasonalHighlight
chosen
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
-
E.
hasSeasonalDecorations
Indicates that an entity is adorned with decorations that are specific to a particular season or holiday period.
- 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_69c68a5ade988190885b7175f63b7534 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f02d36108190bcb34a95e6a30bd7 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:07 p.m.