Triple
T28768716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcel Hirscher |
E726348
|
entity |
| Predicate | WorldCupOverallTitlesConsecutive |
P183717
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Marcel Hirscher, WorldCupOverallTitlesConsecutive, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldCupOverallTitlesConsecutive Context triple: [Marcel Hirscher, WorldCupOverallTitlesConsecutive, 8]
-
A.
WorldCupOverallTitles
Indicates the total number of World Cup championship titles an entity has won across all tournaments.
-
B.
WorldCupSeasonTitles
Indicates the number of World Cup titles an entity has won in a given season or across seasons.
-
C.
WorldCupVictories
Indicates the number of times an entity has won the FIFA World Cup tournament.
-
D.
numberOfWorldCupWins
Indicates how many times an entity has won the FIFA World Cup tournament.
-
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_69f7a283388c81908e4a9ee3369e8d6f |
completed | May 3, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a224365081908ff6958e3b30bd05 |
completed | May 3, 2026, 7:29 p.m. |
Created at: April 28, 2026, 6:14 a.m.