Triple
T22641430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judi Farr |
E558836
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Judi Farr |
—
|
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: Judi Farr | Statement: [Judi Farr, name, Judi Farr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Judi Farr Context triple: [Judi Farr, name, Judi Farr]
-
A.
Judi Farr
chosen
Judi Farr was an Australian actress known for her extensive work in theatre, film, and television, including prominent roles in classic Australian TV comedies and dramas.
-
B.
Lorraine Kirke
Lorraine Kirke is a British-born New York boutique owner and costume designer known for her bohemian fashion aesthetic and as the mother of actress Jemima Kirke.
-
C.
Barbara Feldon
Barbara Feldon is an American actress and former model best known for her role as the stylish and intelligent Agent 99 on the 1960s television comedy series "Get Smart."
-
D.
Penny Calvert
Penny Calvert is a British dancer best known as the first wife of entertainer Bruce Forsyth.
-
E.
Lynn Garland
Lynn Garland is the wife of U.S. Attorney General and former Supreme Court nominee Merrick Garland and is known for her work in public service and community engagement.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f170116fe881908178cffef26e3ae7 |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:04 p.m.