Triple
T38220480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korać Cup |
E1010794
|
entity |
| Predicate | lastSeasonChampionCountry |
P190306
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Korać Cup, lastSeasonChampionCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastSeasonChampionCountry Context triple: [Korać Cup, lastSeasonChampionCountry, France]
-
A.
pennantWinnerHomeCountry
Indicates the country that is considered the home nation of the team that won a particular pennant.
-
B.
WorldCupWinner
Indicates that the subject is the team or individual that won a specified FIFA World Cup tournament.
-
C.
worldCupWinningTeam
Indicates that a team is the champion (winner) of a specific edition of the FIFA World Cup tournament.
-
D.
countryOfLeague
Indicates the country in which a given league is based or officially belongs.
-
E.
countryOfStrongAssociation
Indicates a strong, notable, or primary connection between an entity and a specific country, such as origin, major activity, or significant influence.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc42b9334819099929649b7ef68ea |
completed | May 7, 2026, 4:56 p.m. |
Created at: May 3, 2026, 4:30 p.m.