Triple
T25904167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Women’s Euro 2022 Golden Boot |
E652704
|
entity |
| Predicate | jointTopScorerGoals |
P80657
|
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: [UEFA Women’s Euro 2022 Golden Boot, jointTopScorerGoals, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jointTopScorerGoals Context triple: [UEFA Women’s Euro 2022 Golden Boot, jointTopScorerGoals, 6]
-
A.
topGoalScorerGoals
chosen
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
B.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
C.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
D.
finalGoalscorer
Indicates that an entity is the player who scored the last goal in a particular match or event.
-
E.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f603bd60c08190b6032dff3bdaf5e3 |
completed | May 2, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 22, 2026, 8:26 a.m.