Triple
T7882841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steinberg Skating Rink |
E183022
|
entity |
| Predicate | hasPrimarySeason |
P1014
|
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: [Steinberg Skating Rink, hasPrimarySeason, winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySeason Context triple: [Steinberg Skating Rink, hasPrimarySeason, winter]
-
A.
hasSeason
chosen
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
B.
hasSeasonType
Indicates that something is associated with a particular category or type of season (e.g., summer, winter, rainy).
-
C.
hasImportantSeason
Indicates that an entity experiences a particular season or time period that is especially significant or notable for it.
-
D.
hasSeasonalStatus
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
-
E.
hasHotSeason
Indicates that an entity experiences a distinct period of time characterized by hot or high-temperature weather conditions.
- 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_69ca828af6e48190a06ee7010d8f0e64 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39d36574819092d70e24c37952d7 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae92b0cd881908e715a10d3252e83 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:58 p.m.