Triple
T28322885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flick |
E717324
|
entity |
| Predicate | nationalTeamTournamentCoached |
P149691
|
FINISHED |
| Object | UEFA Euro 2020 (as assistant coach) |
—
|
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: UEFA Euro 2020 (as assistant coach) | Statement: [Flick, nationalTeamTournamentCoached, UEFA Euro 2020 (as assistant coach)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalTeamTournamentCoached Context triple: [Flick, nationalTeamTournamentCoached, UEFA Euro 2020 (as assistant coach)]
-
A.
nationalTeamCoachingDebutYear
Indicates the year in which a coach first officially began coaching a national team.
-
B.
coachedTeamInCountry
Indicates that a person served as a coach for a particular team while that team was based in or associated with a specified country.
-
C.
teamServedAsCoach
Indicates that a person held the role of coach for a particular team.
-
D.
countryCoached
Indicates that a person has served as a coach for a particular country’s team or delegation.
-
E.
teamCoachedToTournament
chosen
Indicates that a coach led or trained a team that participated in a specific tournament.
- 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_69eff6e6c3b08190ad78de6ba7f04548 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 28, 2026, 12:26 a.m.