Triple
T24707728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018–2019 Premier League |
E611942
|
entity |
| Predicate | highestScoringTeam |
P6606
|
FINISHED |
| Object | Manchester City F.C. |
—
|
NE NERFINISHED |
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: Manchester City F.C. | Statement: [2018–2019 Premier League, highestScoringTeam, Manchester City F.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestScoringTeam Context triple: [2018–2019 Premier League, highestScoringTeam, Manchester City F.C.]
-
A.
topScorerTeam
chosen
Indicates that a given team is the one with the highest score (or total points) in a particular game, season, or competition.
-
B.
winningTeamScore
Indicates the number of points or goals achieved by the team that wins a particular game or competition.
-
C.
mostSuccessfulActiveTeam
Indicates that the subject is the currently active team with the highest level of success (e.g., wins, titles, or performance) compared to all other active teams in the relevant context.
-
D.
topTryScorerTeam
Indicates that a team is the one for which a given player is the top try scorer.
-
E.
coachOfScoringTeam
Indicates that one entity is the coach of the team that scored in a particular play or event.
- 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.