Triple
T26924745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intel Grand Slam |
E677746
|
entity |
| Predicate | season3EventLimit |
P2438
|
FINISHED |
| Object | 10 consecutive eligible events |
—
|
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: 10 consecutive eligible events | Statement: [Intel Grand Slam, season3EventLimit, 10 consecutive eligible events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: season3EventLimit Context triple: [Intel Grand Slam, season3EventLimit, 10 consecutive eligible events]
-
A.
numberOfEvents
chosen
Indicates the quantity or count of events associated with a given entity or context.
-
B.
teamLimitInRecentEditions
Indicates a constraint on the number of teams allowed to participate in the most recent editions of a competition or event.
-
C.
capacityDuringEvent
Indicates the maximum number of occupants or usage level that a place, system, or resource can handle specifically during a given event.
-
D.
numberOfMainEvents
Indicates the total count of primary or most significant events associated with a given entity or context.
-
E.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
- 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_69eee9bdebc48190ba90a12a63e09c73 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 27, 2026, 6:09 a.m.