Triple
T32535751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier 5 tournaments |
E831583
|
entity |
| Predicate | hadNumberOfEventsPerSeason |
P12655
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Premier 5 tournaments, hadNumberOfEventsPerSeason, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadNumberOfEventsPerSeason Context triple: [Premier 5 tournaments, hadNumberOfEventsPerSeason, 5]
-
A.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
-
B.
partOfSeasonCount
Indicates that an entity represents the number of parts or segments that make up a particular season.
-
C.
typicalNumberOfMeetingsPerSeason
chosen
Indicates the usual or average count of meetings that occur within a single season.
-
D.
hasSeasonFrequency
Indicates how often something occurs or is scheduled within a specific season.
-
E.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of 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_69f34924b1cc8190ad3aca0c0f012a7e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c57062c481908b041788842c5990 |
completed | May 3, 2026, 3:48 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:01 a.m.