Triple
T24919226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capocannoniere 1996–97 |
E624072
|
entity |
| Predicate | isTopScorerTitleOf |
P157235
|
FINISHED |
| Object | Serie A |
—
|
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: Serie A | Statement: [Capocannoniere 1996–97, isTopScorerTitleOf, Serie A]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTopScorerTitleOf Context triple: [Capocannoniere 1996–97, isTopScorerTitleOf, Serie A]
-
A.
isAmongTopScorers
Indicates that an entity ranks within the highest-performing group based on a scoring or evaluation metric.
-
B.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
C.
hasTopScorersList
Indicates that an entity maintains or is associated with a list of individuals or items ranked as top scorers.
-
D.
countryOfLeagueTopScorerTitle
Indicates the country associated with the league’s top scorer title.
-
E.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
- F. None of above. chosen
Provenance (4 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f4238f98ec8190a4159dcec666fe5a |
completed | May 1, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f423637bec8190a1701421ac86a3b7 |
completed | May 1, 2026, 3:52 a.m. |
Created at: April 18, 2026, 5:28 a.m.