Triple
T26175706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2002 FIFA World Cup third place match against South Korea |
E654533
|
entity |
| Predicate | teamCoachOfTurkey |
P42165
|
FINISHED |
| Object | Şenol Güneş |
—
|
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: Şenol Güneş | Statement: [2002 FIFA World Cup third place match against South Korea, teamCoachOfTurkey, Şenol Güneş]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamCoachOfTurkey Context triple: [2002 FIFA World Cup third place match against South Korea, teamCoachOfTurkey, Şenol Güneş]
-
A.
headCoachOfHomeTeam
Indicates that a person serves as the head coach of the designated home team in a sporting event or competition.
-
B.
coachOf
Indicates that one entity serves as the coach (trainer or manager) of another entity, typically a person or team.
-
C.
headCoachTeam
chosen
Indicates that a person serves as the head coach of a particular team.
-
D.
headCoachFrom
Indicates that one entity serves as the head coach and originates from, or is affiliated with, the location or organization represented by the other entity.
-
E.
headCoachFullName
Indicates the full personal name of the individual who serves as head coach for a given team or organization.
- 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_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 26, 2026, 8:37 p.m.