Triple
T24707723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018–2019 Premier League |
E611942
|
entity |
| Predicate | mostCleanSheets |
P155725
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [2018–2019 Premier League, mostCleanSheets, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostCleanSheets Context triple: [2018–2019 Premier League, mostCleanSheets, 21]
-
A.
mostCleanSheetsNumber
chosen
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
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.
fewestGoalsConcededRecordScope
Indicates the specific context or scope (such as competition, season, or time period) within which a record for the fewest goals conceded is defined.
-
E.
mostWinsGoaltenderWins
Indicates that the goaltender associated with this record holds the highest number of wins compared to all other goaltenders in the relevant context.
- 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_69e2c4d9c24c8190a3712d74327f0c6e |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ee8ada8819089a7016b50308ff0 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:24 a.m.