Triple
T28768765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renate Götschl |
E726349
|
entity |
| Predicate | numberOfWorldCupPodiums |
P200449
|
FINISHED |
| Object | 110 |
—
|
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: 110 | Statement: [Renate Götschl, numberOfWorldCupPodiums, 110]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWorldCupPodiums Context triple: [Renate Götschl, numberOfWorldCupPodiums, 110]
-
A.
WorldChampionshipMedalsTotal
Indicates the total number of medals an entity has won at world championship competitions.
-
B.
numberOfWorldCupWins
Indicates how many times an entity has won the FIFA World Cup tournament.
-
C.
worldCupPodiums
Indicates that one entity has achieved podium (top-three) finishes in FIFA World Cup competitions, with the related entity specifying those podium results.
-
D.
numberOfWorldCupVictories
Indicates the count of FIFA World Cup tournament titles that an entity (typically a national team or country) has won.
-
E.
WorldCupMedal
Indicates that an entity has received a medal (e.g., gold, silver, bronze) for its performance in a 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_69f03198be14819098fa74e48b3749bf |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69ff8ba3f8248190bbdf8e7ec2b35093 |
completed | May 9, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69ff8b41ba988190a7332e8317d10f09 |
completed | May 9, 2026, 7:30 p.m. |
| PDg | Predicate description generation | batch_69ff8ba329e08190813e728f0d1bd973 |
completed | May 9, 2026, 7:31 p.m. |
Created at: April 28, 2026, 6:14 a.m.