Triple
T28768770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renate Götschl |
E726349
|
entity |
| Predicate | WorldCupOverallSeasonsRunnerUp |
P184850
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Renate Götschl, WorldCupOverallSeasonsRunnerUp, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldCupOverallSeasonsRunnerUp Context triple: [Renate Götschl, WorldCupOverallSeasonsRunnerUp, 3]
-
A.
WorldCupRunnerUp
Indicates that an entity finished in second place in a FIFA World Cup tournament, losing in the final match.
-
B.
worldCupRunnerUp
Indicates that an entity finished in second place in a FIFA World Cup tournament.
-
C.
WorldCupVictories
Indicates the number of times an entity has won the FIFA World Cup tournament.
-
D.
WorldCupOverallTitlesConsecutive
Indicates the number of times an entity has won World Cup overall titles in consecutive editions without interruption.
-
E.
WorldCupWins
Indicates the number of times an entity (typically a national team) has won the 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_69f7b628b17c8190aa058c1a51852a27 |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b5cadd308190a864245a21b08f9a |
completed | May 3, 2026, 8:53 p.m. |
Created at: April 28, 2026, 6:14 a.m.