Triple
T27797493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier League 2011–12 with Manchester City |
E702153
|
entity |
| Predicate | topScorerGoalsLeague |
P80657
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Premier League 2011–12 with Manchester City, topScorerGoalsLeague, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topScorerGoalsLeague Context triple: [Premier League 2011–12 with Manchester City, topScorerGoalsLeague, 23]
-
A.
topGoalScorerGoals
chosen
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
B.
premierLeagueGoals
Indicates the number of goals an entity has scored in the Premier League.
-
C.
seasonTopScorerTeam1
Indicates that the referenced entity is the team whose player was the top scorer for team 1 in a given season.
-
D.
rankAllTimeGoals
Indicates a relationship that orders entities based on the total number of goals they have scored across all time.
-
E.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular 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_69ef8408e0588190977cffa32dc33a29 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63894e5848190aec428392562ab06 |
completed | May 2, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69f6370c8c7c8190a02ea82847bb6e76 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 5:32 p.m.