Triple
T24675284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1988 Rugby League World Cup |
E610966
|
entity |
| Predicate | winnerTitleCountForAustralia |
P25122
|
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: [1988 Rugby League World Cup, winnerTitleCountForAustralia, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerTitleCountForAustralia Context triple: [1988 Rugby League World Cup, winnerTitleCountForAustralia, 6]
-
A.
numberOfAustralianChampionships
Indicates the count of Australian Championships that an entity has won or holds.
-
B.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
-
C.
AustraliaCupTitles
Indicates the number of Australia Cup titles a team or entity has won.
-
D.
winnerTitleRecord
Indicates that a record documents the title or achievement associated with an entity that has won a particular contest, award, or competition.
-
E.
countryWithMostTitles
Indicates the country that holds the highest number of titles (e.g., championships or awards) within a specified competition or context.
- 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_69e2c4d5c2dc8190ac857dea25ec6ce9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:03 a.m.