Triple
T32625339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FA Cup 1903 |
E834039
|
entity |
| Predicate | numberOfGoalsByWinnerInFinal |
P198406
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [FA Cup 1903, numberOfGoalsByWinnerInFinal, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsByWinnerInFinal Context triple: [FA Cup 1903, numberOfGoalsByWinnerInFinal, 6]
-
A.
scoredGoalsInFinalOf
Indicates that one entity scored one or more goals in the final match of a specified competition or event.
-
B.
finalScoreWinnerGoals
chosen
Indicates the number of goals scored by the winning side in the final score of a match or game.
-
C.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
-
D.
worldCupFinalScore
Indicates the final score outcome of a FIFA World Cup match, typically specifying the number of goals each team scored by the end of the final game.
-
E.
winnerSetsWonInFinal
Indicates the number of sets won by the winning participant in the final match of a competition.
- 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_69f3492ccc80819086ef7d26e9786647 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a01c5c5dbb881909b19ba87a7760ee7 |
completed | May 11, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_6a01c549af98819098e0effd775b7710 |
completed | May 11, 2026, 12:02 p.m. |
Created at: May 1, 2026, 1:06 a.m.