Triple
T35713657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1968 European Cup Final |
E1031937
|
entity |
| Predicate | goalScorerForBenfica |
P2695
|
FINISHED |
| Object | Jaime Graça |
—
|
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: Jaime Graça | Statement: [1968 European Cup Final, goalScorerForBenfica, Jaime Graça]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalScorerForBenfica Context triple: [1968 European Cup Final, goalScorerForBenfica, Jaime Graça]
-
A.
numberOfGoalsForBenfica
Indicates the total number of goals that were scored by Benfica in the given context or event.
-
B.
numberOfAppearancesForBenfica
Indicates the number of times an entity has appeared in matches for the Benfica football club.
-
C.
playedForBenficaBetween
Indicates that an entity was a player for Benfica during a specified time period.
-
D.
aggregateScoreVsBenfica
Indicates the overall combined score achieved in matches played against Benfica across all relevant legs or encounters.
-
E.
goalScorer
chosen
Indicates that the subject is the player who scored a particular goal in a game or match.
- 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_69f76e0df1d08190965b1c6dff94c391 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:05 p.m.