Triple
T31963284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvan Zurbriggen |
E816103
|
entity |
| Predicate | worldChampionshipTeams |
P194616
|
FINISHED |
| Object | Switzerland |
—
|
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: Switzerland | Statement: [Silvan Zurbriggen, worldChampionshipTeams, Switzerland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldChampionshipTeams Context triple: [Silvan Zurbriggen, worldChampionshipTeams, Switzerland]
-
A.
nationalTeamChampionships
Indicates the number of championship titles an entity has won at the national team level.
-
B.
nationalTeamTitles
Indicates the number of titles or championships an entity has won while representing its national team.
-
C.
team2ChampionshipHistory
Indicates the record of championships that the second team has participated in or won over time.
-
D.
worldCupWinningTeam
Indicates that a team is the champion (winner) of a specific edition of the FIFA World Cup tournament.
-
E.
WorldCupWinner
Indicates that the subject is the team or individual that won a specified FIFA World Cup tournament.
- F. None of above. chosen
Provenance (4 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_69f348f4ec708190abbb2a7c3ed58844 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd7e364a648190a1e9e1d9fc76e99e |
completed | May 8, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69fd7bb547608190a3b04dddbca6b8bc |
completed | May 8, 2026, 5:59 a.m. |
| PDg | Predicate description generation | batch_69fd7e35967081909f8bc8389d976ffd |
completed | May 8, 2026, 6:09 a.m. |
Created at: May 1, 2026, 12:09 a.m.