Triple
T12054553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teófilo Cubillas |
E287005
|
entity |
| Predicate | FIFAWorldCupGoalsRank |
P102973
|
FINISHED |
| Object | one of the highest-scoring midfielders in World Cup history |
—
|
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: one of the highest-scoring midfielders in World Cup history | Statement: [Teófilo Cubillas, FIFAWorldCupGoalsRank, one of the highest-scoring midfielders in World Cup history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FIFAWorldCupGoalsRank Context triple: [Teófilo Cubillas, FIFAWorldCupGoalsRank, one of the highest-scoring midfielders in World Cup history]
-
A.
worldCupGoals
Indicates the number of goals an entity scored in World Cup matches.
-
B.
rankAllTimeGoals
Indicates a relationship that orders entities based on the total number of goals they have scored across all time.
-
C.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
D.
fifaCenturyGoals
Indicates that a player has scored at least 100 goals in official FIFA-recognized international matches.
-
E.
fifaWorldRankingPeakPosition
Indicates the highest (best) position an entity has ever achieved in the official FIFA world rankings.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:47 p.m.