Triple
T26175701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2002 FIFA World Cup third place match against South Korea |
E654533
|
entity |
| Predicate | numberOfGoalsByTurkey |
P9098
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [2002 FIFA World Cup third place match against South Korea, numberOfGoalsByTurkey, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsByTurkey Context triple: [2002 FIFA World Cup third place match against South Korea, numberOfGoalsByTurkey, 3]
-
A.
TurkishSuperCupTitles
Indicates the number of Turkish Super Cup titles that an entity (typically a football club) has won.
-
B.
resultForTurkey
Indicates that something is the outcome, consequence, or result specifically associated with Turkey.
-
C.
previousMatchForTurkey
Indicates that one entity is a match that occurred immediately before another match involving Turkey.
-
D.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
E.
numberOfTurkishCups
Indicates the quantity of Turkish cups associated with or involved in a given entity or context.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
Created at: April 26, 2026, 8:37 p.m.