Triple
T31963285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvan Zurbriggen |
E816103
|
entity |
| Predicate | worldChampionshipYears |
P133707
|
FINISHED |
| Object | 2003 |
—
|
LITERAL FINISHED |
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: 2003 | Statement: [Silvan Zurbriggen, worldChampionshipYears, 2003]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldChampionshipYears Context triple: [Silvan Zurbriggen, worldChampionshipYears, 2003]
-
A.
worldChampionshipMatchYear
Indicates the year in which a given world championship match took place.
-
B.
worldChampionshipTitleYear
chosen
Indicates the specific year in which an entity won a world championship title.
-
C.
lastWorldChampionshipEditionYear
Indicates the calendar year in which the most recent edition of a given world championship event took place.
-
D.
worldChampionshipFrequency
Indicates how often a world championship event is held or occurs over a given period.
-
E.
worldChampionshipBestYear
Indicates the year in which an entity achieved its best or most successful performance in a world championship competition.
- 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_69f348f4ec708190abbb2a7c3ed58844 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: May 1, 2026, 12:09 a.m.