Triple
T11114343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women's Rugby World Cup |
E262844
|
entity |
| Predicate | numberOfTitlesWonByMostSuccessfulTeam |
P27144
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Women's Rugby World Cup, numberOfTitlesWonByMostSuccessfulTeam, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTitlesWonByMostSuccessfulTeam Context triple: [Women's Rugby World Cup, numberOfTitlesWonByMostSuccessfulTeam, 6]
-
A.
numberOfTitlesOfMostSuccessfulClub
chosen
Indicates the total count of titles won by the club that has achieved the highest number of titles among all clubs in the given context.
-
B.
mostTitlesTeamTitles
Indicates that the referenced team holds the highest number of titles compared to all other teams in the specified context.
-
C.
mostChampionshipTitlesClub
Indicates that a club holds the highest number of championship titles within a given competition or context.
-
D.
numberOfLeagueTitles
Indicates the total count of league championship titles that an entity has won.
-
E.
consecutiveLeagueTitles
Indicates that one entity has won league titles in successive seasons without interruption.
- F. None of above.
Provenance (3 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79aa637888190935e852281408356 |
completed | April 9, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69d7441cf8188190b8095f622c923156 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.