Triple
T20254370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leah Purcell |
E498646
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Leah Purcell |
—
|
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: Leah Purcell | Statement: [Leah Purcell, name, Leah Purcell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leah Purcell Context triple: [Leah Purcell, name, Leah Purcell]
-
A.
Leah Purcell
chosen
Leah Purcell is an acclaimed Australian actor, writer, and director known for her powerful performances and contributions to Indigenous storytelling in film, television, and theatre.
-
B.
Kate Mulvany
Kate Mulvany is an Australian actress, playwright, and screenwriter known for her work across theatre, film, and television.
-
C.
Kerry Bishé
Kerry Bishé is a New Zealand–born American actress best known for her roles in the film "Argo" and the television series "Halt and Catch Fire."
-
D.
Tania Tapsell
Tania Tapsell is a New Zealand politician and local government leader known for serving as the mayor of Rotorua and for her prominence as a young Māori woman in public office.
-
E.
Rebecca Herbst
Rebecca Herbst is an American actress best known for her long-running role as nurse Elizabeth Webber on the soap opera "General Hospital."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673aa42348190852ae8313f4494ca |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:41 p.m.