Triple
T23688732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Champions League 2004–05 |
E585240
|
entity |
| Predicate | hasTopScorer |
P6605
|
FINISHED |
| Object | Ruud van Nistelrooy |
—
|
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: Ruud van Nistelrooy | Statement: [UEFA Champions League 2004–05, hasTopScorer, Ruud van Nistelrooy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTopScorer Context triple: [UEFA Champions League 2004–05, hasTopScorer, Ruud van Nistelrooy]
-
A.
topScorer
chosen
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
B.
isAmongTopScorers
Indicates that an entity ranks within the highest-performing group based on a scoring or evaluation metric.
-
C.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
-
D.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
E.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or 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_69e249037ce0819088b149608e98f685 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b5bfe15c8190af2b4c451bccae16 |
completed | April 29, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:52 p.m.