Triple
T2181874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australia national rugby union team |
E49061
|
entity |
| Predicate | worldRugbyRankingBest |
P37698
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Australia national rugby union team, worldRugbyRankingBest, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldRugbyRankingBest Context triple: [Australia national rugby union team, worldRugbyRankingBest, 1]
-
A.
fifaRankingHighest
Indicates that the subject has the highest FIFA ranking among a specified group or within a given context.
-
B.
globalRanking
Indicates the position or status of an entity relative to all comparable entities worldwide according to some ranking criteria.
-
C.
fifaRankingHighestDate
Indicates the date on which an entity achieved its highest-ever FIFA ranking.
-
D.
FIFARankingWorst
Indicates that the subject has the lowest (worst) FIFA ranking among a specified set of entities.
-
E.
WorldCupVictories
Indicates the number of times an entity 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc434978c8190b9c4dd8411b87f23 |
completed | March 7, 2026, 6:22 a.m. |
Created at: March 4, 2026, 7:45 p.m.