Triple
T35920595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winter (from the Four Seasons) |
E1038871
|
entity |
| Predicate | hasSeasonRepresented |
P144678
|
FINISHED |
| Object | winter |
—
|
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: winter | Statement: [Winter (from the Four Seasons), hasSeasonRepresented, winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonRepresented Context triple: [Winter (from the Four Seasons), hasSeasonRepresented, winter]
-
A.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
B.
hasSeasonRelation
chosen
Indicates a relationship where one entity is associated with another through a specific season or seasonal context (e.g., occurring in, relevant to, or characteristic of that season).
-
C.
hasPartOfSeason
Indicates that one season includes another season or a segment of a season as a constituent part.
-
D.
wonSeasonOf
Indicates that one entity emerged as the overall winner of a particular season of a competition, show, or series involving the other entity.
-
E.
hasSeasonType
Indicates that something is associated with a particular category or type of season (e.g., summer, winter, rainy).
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0031ed5d708190ab93516ad081ada6 |
completed | May 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_6a0031b5dbd081908eb0f4dbb8a0eac3 |
completed | May 10, 2026, 7:20 a.m. |
Created at: May 3, 2026, 4:07 p.m.