Triple
T27770402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016–17 Serie A with Juventus FC |
E701727
|
entity |
| Predicate | topScorerForClubInLeague |
P73904
|
FINISHED |
| Object | Gonzalo Higuaín |
—
|
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: Gonzalo Higuaín | Statement: [2016–17 Serie A with Juventus FC, topScorerForClubInLeague, Gonzalo Higuaín]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topScorerForClubInLeague Context triple: [2016–17 Serie A with Juventus FC, topScorerForClubInLeague, Gonzalo Higuaín]
-
A.
seasonTopScorerTeam1
Indicates that the referenced entity is the team whose player was the top scorer for team 1 in a given season.
-
B.
leagueTopScorerTeam
Indicates the team for which a given league’s top-scoring player plays or played.
-
C.
leagueTopScorerInSeason
chosen
Indicates that an entity was the highest goal/point scorer in a particular league during a specified season.
-
D.
mostPointsClub
Indicates that a club holds the highest number of points compared to all other clubs in the relevant context.
-
E.
topScorerCompetition
Indicates that an entity is the highest-scoring participant in a specified competition.
- 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_69ef6a52fa708190934a32308d2c92dc |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f637962be88190b63239f6e4b782f4 |
completed | May 2, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69f63188e7408190af8ce8b93d128c63 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 4:34 p.m.