Triple
T20993713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia McKenzie |
E517089
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Julia McKenzie |
—
|
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: Julia McKenzie | Statement: [Julia McKenzie, name, Julia McKenzie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julia McKenzie Context triple: [Julia McKenzie, name, Julia McKenzie]
-
A.
Julia McKenzie
chosen
Julia McKenzie is an English actress and singer known for her work in musical theatre, television, and film, including her portrayal of Miss Marple in the Agatha Christie's Marple series.
-
B.
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.
-
C.
Claire Jackman
Claire Jackman is a fictional character portrayed by actress Gina Bellman, known from her work in British television and film.
-
D.
Kate Mulvany
Kate Mulvany is an Australian actress, playwright, and screenwriter known for her work across theatre, film, and television.
-
E.
Suzanne Mackie
Suzanne Mackie is a British television and film producer known for her work on acclaimed projects such as "The Crown" and other high-profile UK dramas.
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc1d829081908de889c542734393 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:50 p.m.