Triple
T28725216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hans-Dieter Flick |
E730202
|
entity |
| Predicate | wonCompetitionAsAssistantCoach |
P80808
|
FINISHED |
| Object | 2014 FIFA World Cup |
—
|
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: 2014 FIFA World Cup | Statement: [Hans-Dieter Flick, wonCompetitionAsAssistantCoach, 2014 FIFA World Cup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonCompetitionAsAssistantCoach Context triple: [Hans-Dieter Flick, wonCompetitionAsAssistantCoach, 2014 FIFA World Cup]
-
A.
wonChampionshipAsAssistantCoachWith
Indicates that one entity served as an assistant coach on a team that won a championship together with the other entity.
-
B.
championshipWonAsCoach
Indicates that the subject, acting in the role of coach, has won a championship title with the associated team or organization.
-
C.
medalWonAsCoach
Indicates that an individual has won a medal in the role of a coach rather than as a competitor.
-
D.
notableAchievementAsCoach
Indicates that the subject has a significant or distinguished accomplishment specifically in their role as a coach.
-
E.
worldCupTitlesAsAssistantCoach
chosen
Indicates the number of FIFA World Cup titles an individual has won specifically in the role of assistant coach.
- 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f658ee40088190b71e1219407690d0 |
completed | May 2, 2026, 8:05 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 5:55 a.m.