Triple
T22742288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier League 2007–08 |
E562443
|
entity |
| Predicate | fewestGoalsTeamGoals |
P9098
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Premier League 2007–08, fewestGoalsTeamGoals, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fewestGoalsTeamGoals Context triple: [Premier League 2007–08, fewestGoalsTeamGoals, 20]
-
A.
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.
-
B.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
C.
goalsConceded
Indicates the number of goals a team or player has allowed the opposing side to score.
-
D.
mostLossesTeam
Indicates the team that has incurred the greatest number of losses within a given set of teams or season.
-
E.
goalScorerTeam
Indicates that a team is the one for which a particular goal scorer scored a goal.
- 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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1797400fc8190bec26726f434f787 |
completed | April 29, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69eed2a971c0819088af574e40c9343f |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:23 p.m.