Triple
T29113180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gregor Schlierenzauer |
E736966
|
entity |
| Predicate | hasWorldCupTitles |
P31745
|
FINISHED |
| Object | multiple overall World Cup titles in ski jumping |
—
|
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: multiple overall World Cup titles in ski jumping | Statement: [Gregor Schlierenzauer, hasWorldCupTitles, multiple overall World Cup titles in ski jumping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorldCupTitles Context triple: [Gregor Schlierenzauer, hasWorldCupTitles, multiple overall World Cup titles in ski jumping]
-
A.
WorldCupOverallTitles
chosen
Indicates the total number of World Cup championship titles an entity has won across all tournaments.
-
B.
numberOfWorldCupWins
Indicates how many times an entity has won the FIFA World Cup tournament.
-
C.
worldCupWon
Indicates that the subject has won the FIFA World Cup tournament.
-
D.
hasWonCupTitles
Indicates that an entity has achieved victory in one or more cup-style competitions, resulting in official cup titles.
-
E.
hasWorldCupOverallTitleRecord
Indicates that one entity holds the record for the most overall World Cup titles in comparison to others.
- 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_69f077ed54e08190bb02a744e8121a66 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
Created at: April 28, 2026, 11:20 a.m.