Triple
T24580195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheelchair Rugby League World Cup |
E608225
|
entity |
| Predicate | 2021EditionRunnerUp |
P2683
|
FINISHED |
| Object | France national wheelchair rugby league team |
—
|
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 national wheelchair rugby league team | Statement: [Wheelchair Rugby League World Cup, 2021EditionRunnerUp, France national wheelchair rugby league team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 2021EditionRunnerUp Context triple: [Wheelchair Rugby League World Cup, 2021EditionRunnerUp, France national wheelchair rugby league team]
-
A.
conferenceOfRunnerUp
Indicates the conference or league affiliation to which the runner-up entity belongs.
-
B.
runnerUp
chosen
Indicates that one entity finished in second place relative to another in a competition or ranking.
-
C.
secondEditionRunnerUp
Indicates that an entity finished as the runner-up (second place) in the second edition of a particular event or competition.
-
D.
runnerUpCountry
Indicates the country that finished in second place in a competition or ranking.
-
E.
runnerUpSchool
Indicates that a school finished in second place (as the runner-up) in a specified competition or event.
- 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_69e2c4ce89248190ad99e18f0638dfbb |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a97fde9c81909d8de91b6358a015 |
completed | April 30, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:29 a.m.