Triple
T23032345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne |
E573496
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Penelope Wilton |
—
|
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: Penelope Wilton | Statement: [Anne, portrayedBy, Penelope Wilton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penelope Wilton Context triple: [Anne, portrayedBy, Penelope Wilton]
-
A.
Penelope Wilton
chosen
Penelope Wilton is an English actress known for her acclaimed work in film, television, and theatre, including roles in "Downton Abbey" and "The Best Exotic Marigold Hotel."
-
B.
Louise Plowright
Louise Plowright was a British actress known for her work in television and musical theatre, including notable roles in West End productions.
-
C.
Patricia Routledge
Patricia Routledge is an English actress and comedian best known for her acclaimed stage work and for starring as the snobbish Hyacinth Bucket in the sitcom "Keeping Up Appearances."
-
D.
Betsy Aidem
Betsy Aidem is an American actress known for her work in film, television, and theater.
-
E.
Lesley Garrett
Lesley Garrett is an English soprano and media personality known for her operatic performances and popular classical crossover work.
- 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_69e245b911188190bc3d96326c847969 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f184822a90819081907d72c76770b0 |
completed | April 29, 2026, 4:09 a.m. |
Created at: April 17, 2026, 3:53 p.m.