Triple
T26004057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico 1–0 Germany at 2018 FIFA World Cup group stage |
E646708
|
entity |
| Predicate | teamCoachMexico |
P42165
|
FINISHED |
| Object | Juan Carlos Osorio |
—
|
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: Juan Carlos Osorio | Statement: [Mexico 1–0 Germany at 2018 FIFA World Cup group stage, teamCoachMexico, Juan Carlos Osorio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamCoachMexico Context triple: [Mexico 1–0 Germany at 2018 FIFA World Cup group stage, teamCoachMexico, Juan Carlos Osorio]
-
A.
MexicanCounterpartTeam
Indicates a team that serves as the Mexican counterpart or equivalent to another team in a corresponding role, function, or context.
-
B.
teamChampionHeadCoach
Indicates that a coach served as the head coach of a team during a season or event in which that team won a championship.
-
C.
coachOf
Indicates that one entity serves as the coach (trainer or manager) of another entity, typically a person or team.
-
D.
headCoachTeam
chosen
Indicates that a person serves as the head coach of a particular team.
-
E.
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.
- 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_69e77e89d5848190b54352cdb74f6029 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f60577c7188190b9a5fef79c150176 |
completed | May 2, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 22, 2026, 9 a.m.