Triple
T16533750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DDR-Oberliga |
E401631
|
entity |
| Predicate | hadSeasonalSchedule |
P15928
|
FINISHED |
| Object | winter months |
—
|
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 months | Statement: [DDR-Oberliga, hadSeasonalSchedule, winter months]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSeasonalSchedule Context triple: [DDR-Oberliga, hadSeasonalSchedule, winter months]
-
A.
hasSeasonalPattern
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
B.
hasSeasonalStatus
chosen
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
-
C.
hasSeasonalRound
Indicates a recurring, seasonally patterned cycle of movements, activities, or resource use associated with an entity over the course of a year.
-
D.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
E.
hasSeasonalStructure
Indicates that something exhibits a recurring pattern, organization, or behavior that varies systematically with the seasons.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32eda42548190be61efb25a44a554 |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:15 a.m.