Triple
T37369906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France vs New Zealand |
E927808
|
entity |
| Predicate | team2WorldCupWinner |
P187789
|
FINISHED |
| Object | multiple Rugby World Cup titles |
—
|
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 Rugby World Cup titles | Statement: [France vs New Zealand, team2WorldCupWinner, multiple Rugby World Cup titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: team2WorldCupWinner Context triple: [France vs New Zealand, team2WorldCupWinner, multiple Rugby World Cup titles]
-
A.
worldCupWinningTeam
Indicates that a team is the champion (winner) of a specific edition of the FIFA World Cup tournament.
-
B.
worldCupWonWithTeam
Indicates that an individual won a World Cup tournament while being a member of a specified team.
-
C.
WorldCupWinner
Indicates that the subject is the team or individual that won a specified FIFA World Cup tournament.
-
D.
worldCupWinnerWith
Indicates that one entity is the winner of a specified FIFA World Cup tournament associated with the other entity.
-
E.
worldCupWon
Indicates that the subject 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb8c38a9688190be524246f5682107 |
completed | May 6, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9c6e0481908565bd849e869b24 |
completed | May 6, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_69fb8c37931c81909da038c18ed9add2 |
completed | May 6, 2026, 6:45 p.m. |
Created at: May 3, 2026, 4:16 p.m.