Triple
T28212871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Cinque |
E711221
|
entity |
| Predicate | countryWhereCaseBecameNotable |
P76513
|
FINISHED |
| Object | Australia |
—
|
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: Australia | Statement: [Joe Cinque, countryWhereCaseBecameNotable, Australia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryWhereCaseBecameNotable Context triple: [Joe Cinque, countryWhereCaseBecameNotable, Australia]
-
A.
countryWhereOccurred
Indicates the country in which a particular event, action, or occurrence took place.
-
B.
notableCaseArea
chosen
Indicates that a particular geographic area is notably associated with, or significantly involved in, a given case or legal matter.
-
C.
notableSupremeCourtCase
Indicates that a legal case is recognized as a significant or influential decision by the Supreme Court.
-
D.
notableInRegion
Indicates that an entity is recognized as notable, prominent, or significant within a specified geographic region.
-
E.
notableCountry
Indicates that a country holds particular significance or prominence in relation to the subject entity.
- 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fe066d62b48190867df334039be786 |
completed | May 8, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69fe03afde3c8190a5b9b0778d19eb1a |
completed | May 8, 2026, 3:39 p.m. |
Created at: April 27, 2026, 10:40 p.m.