Triple
T10100330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Kilda Football Club |
E216182
|
entity |
| Predicate | grandFinalAppearancesAFLVFL |
P23920
|
FINISHED |
| Object | multiple |
—
|
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 | Statement: [St Kilda Football Club, grandFinalAppearancesAFLVFL, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandFinalAppearancesAFLVFL Context triple: [St Kilda Football Club, grandFinalAppearancesAFLVFL, multiple]
-
A.
AFLChampionshipGameAppearances
chosen
Indicates the number of times an entity has participated in an AFL championship game.
-
B.
lastVFL_AFLCertifiedPremiership
Indicates the most recent VFL/AFL premiership title that an entity has officially won and been certified as a premiership.
-
C.
AFLChampionships
Indicates the number of AFL championship titles that a team has won.
-
D.
AFLGamesPlayed
Indicates the number of Australian Football League (AFL) games that an entity has participated in.
-
E.
AFLWPremierships
Indicates the number of AFL Women's league premiership titles an entity has won.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd09878f88190bcfa2c81fb10e821 |
completed | April 2, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:02 p.m.