Triple
T32625354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FA Cup 1903 |
E834039
|
entity |
| Predicate | winnerCleanSheetsInCompetition |
P72349
|
FINISHED |
| Object | all 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: all matches | Statement: [FA Cup 1903, winnerCleanSheetsInCompetition, all matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerCleanSheetsInCompetition Context triple: [FA Cup 1903, winnerCleanSheetsInCompetition, all matches]
-
A.
mostCleanSheetsNumber
Indicates the number of times an entity holds the record for having the most clean sheets (games without conceding a goal) in a given context or competition.
-
B.
mostCleanSheetsClub
chosen
Indicates that the club holds the record for the highest number of clean sheets (matches without conceding a goal) in a given context.
-
C.
mostCleanSheetsByGoalkeeper
Indicates that the subject goalkeeper holds the record for the highest number of matches completed without conceding a goal.
-
D.
wonLeagueCup
Indicates that a team or competitor achieved victory in a specific league cup competition or tournament.
-
E.
superLeagueGrandFinalWins
Indicates the number of times an entity has won the Super League Grand Final.
- 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_69f3492ccc80819086ef7d26e9786647 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: May 1, 2026, 1:06 a.m.