Triple
T12843098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sky Bet Championship |
E307101
|
entity |
| Predicate | mostCommonMatchDays |
P54540
|
FINISHED |
| Object | weekends |
—
|
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: weekends | Statement: [Sky Bet Championship, mostCommonMatchDays, weekends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostCommonMatchDays Context triple: [Sky Bet Championship, mostCommonMatchDays, weekends]
-
A.
mostCommonMatchDay
chosen
Indicates the day of the week on which matches most frequently occur for a given set of matches or competition.
-
B.
typicalMatchDay
Indicates that the relationship or conditions described correspond to what normally happens on a standard or usual match day.
-
C.
matchupFrequency
Indicates how often a particular pair or set of entities are matched or paired against each other within a given context or timeframe.
-
D.
typicalNumberOfMatchesPerSeries
Indicates the usual or standard count of matches that are played within a single series.
-
E.
typicalMonthOfOccurrence
Indicates the month in which something most commonly or typically occurs.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:35 p.m.