Triple
T12929120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonel Sánchez |
E309325
|
entity |
| Predicate | sharedTopScorerGoals |
P80657
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Leonel Sánchez, sharedTopScorerGoals, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharedTopScorerGoals Context triple: [Leonel Sánchez, sharedTopScorerGoals, 4]
-
A.
topGoalScorerGoals
chosen
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
B.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
C.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
D.
rankAllTimeGoals
Indicates a relationship that orders entities based on the total number of goals they have scored across all time.
-
E.
FIFAWorldCupGoalsRank
Indicates the ranking of entities based on the number of goals they have scored in FIFA World Cup competitions.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.