Triple
T25475811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eusébio |
E638430
|
entity |
| Predicate | numberOfGoalsForBenfica |
P181721
|
FINISHED |
| Object | 473 |
—
|
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: 473 | Statement: [Eusébio, numberOfGoalsForBenfica, 473]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsForBenfica Context triple: [Eusébio, numberOfGoalsForBenfica, 473]
-
A.
aggregateScoreVsBenfica
Indicates the overall combined score achieved in matches played against Benfica across all relevant legs or encounters.
-
B.
playedForBenficaBetween
Indicates that an entity was a player for Benfica during a specified time period.
-
C.
goalsForPorto
Indicates the number of goals that were scored by the team Porto in a given match or context.
-
D.
PortugalGoalscorer
Indicates that an entity is a player who scored a goal for the Portugal national football team in a given match or context.
-
E.
portugalScore
Indicates that a scoring event or point total is attributed to Portugal in a given context (such as a match, game, or competition).
- 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_69e75db9b964819096802dcf502e577e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7824dc3f0819092a5102895b4a478 |
completed | May 3, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f7817c79e081908e685c48165e086b |
completed | May 3, 2026, 5:10 p.m. |
Created at: April 21, 2026, 2:26 p.m.