Triple
T38473297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ANZ Championship |
E915477
|
entity |
| Predicate | numberOfAustralianTeams |
P204669
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [ANZ Championship, numberOfAustralianTeams, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAustralianTeams Context triple: [ANZ Championship, numberOfAustralianTeams, 5]
-
A.
AllAustralianTeam
Indicates that an entity has been selected for inclusion in the All-Australian Team, representing top-level recognition in Australian rules football for a given period.
-
B.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
C.
numberOfTeamsInCanada
Indicates the total count of teams that are located in Canada.
-
D.
numberOfTeamsInUnitedStates
Indicates the total count of teams that are located within or belong to the United States.
-
E.
qualifiedTeamsCount
Indicates the number of teams that have successfully met the criteria to qualify for a given stage, event, or competition.
- 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:31 p.m.