Triple
T26175703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2002 FIFA World Cup third place match against South Korea |
E654533
|
entity |
| Predicate | fastestGoalScorer |
P160015
|
FINISHED |
| Object | Hakan Şükür |
—
|
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: Hakan Şükür | Statement: [2002 FIFA World Cup third place match against South Korea, fastestGoalScorer, Hakan Şükür]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fastestGoalScorer Context triple: [2002 FIFA World Cup third place match against South Korea, fastestGoalScorer, Hakan Şükür]
-
A.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
B.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
C.
notableGoalScorer
Indicates that the subject is recognized for having scored a significant or noteworthy number of goals, typically in a sports context.
-
D.
recordGoalsHolder
Indicates that the subject entity holds the record for the highest number of goals scored in a given context.
-
E.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60c6bc408819098c4288f77d75e38 |
completed | May 2, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 26, 2026, 8:37 p.m.