Triple
T18271271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier League fixtures |
E437619
|
entity |
| Predicate | typicalSeasonMatchCount |
P97461
|
FINISHED |
| Object | 380 matches |
—
|
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: 380 matches | Statement: [Premier League fixtures, typicalSeasonMatchCount, 380 matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSeasonMatchCount Context triple: [Premier League fixtures, typicalSeasonMatchCount, 380 matches]
-
A.
totalMatchesPerSeason
Indicates the total number of matches associated with an entity within a single season.
-
B.
typicalNumberOfMatchesPerSeries
chosen
Indicates the usual or standard count of matches that are played within a single series.
-
C.
typicalNumberOfMeetingsPerSeason
Indicates the usual or average count of meetings that occur within a single season.
-
D.
typicalMatchDay
Indicates that the relationship or conditions described correspond to what normally happens on a standard or usual match day.
-
E.
totalMatchesPlayed
Indicates the total number of matches that have been played by the referenced entity or between the related entities.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7e00548190a28916a696831336 |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.