Triple
T32996133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waldyr Pereira |
E844234
|
entity |
| Predicate | numberOfGoalsForBrazil |
P203877
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Waldyr Pereira, numberOfGoalsForBrazil, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsForBrazil Context triple: [Waldyr Pereira, numberOfGoalsForBrazil, 20]
-
A.
goalsByBrazil
Indicates the number of goals that Brazil scored in a given match or context.
-
B.
BrazilWorldCupTitlesBeforeMatch
Indicates the number of FIFA World Cup titles Brazil had already won prior to the referenced match.
-
C.
BrazilCameFromBehind
Indicates that Brazil was initially trailing in a contest or match but later overcame the deficit to take the lead or win.
-
D.
penaltyGoalScorerForBrazil
Indicates that the subject is the player who scored a goal from a penalty kick for the Brazil national team.
-
E.
BrazilGoalsByNeymar
Indicates the number of goals scored by Neymar for the Brazil national football team.
- 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_69f3494d99988190b502c68926af2c4d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0235be932081908857bc3a77c27e7d |
completed | May 11, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_6a022c865dec81909e02b2f330e987e6 |
completed | May 11, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_6a0235bd9f5481908d9a173517211119 |
completed | May 11, 2026, 8:02 p.m. |
Created at: May 1, 2026, 1:22 a.m.