Triple
T35872804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberliga (ice hockey) |
E1037273
|
entity |
| Predicate | numberOfRegionalGroupsVariesBySeason |
P124030
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Oberliga (ice hockey), numberOfRegionalGroupsVariesBySeason, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegionalGroupsVariesBySeason Context triple: [Oberliga (ice hockey), numberOfRegionalGroupsVariesBySeason, true]
-
A.
numberOfRegionalGroupingsInLeague
Indicates the total count of distinct regional groupings that exist within a given league.
-
B.
regionalGrouping
Indicates that entities are organized or associated together based on shared geographic or regional characteristics.
-
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.
regionCountVariesBy
chosen
Indicates that the number of regions associated with an entity changes depending on another specified factor or condition.
-
E.
typicalNumberOfStopsPerSeason
Indicates the usual or average count of stops that occur in a single season.
- 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_69f76e1e701c8190a4990d4978ce4fe6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.