Triple
T16027504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggie Macfadyen |
E388754
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Maggie Macfadyen |
—
|
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: Maggie Macfadyen | Statement: [Maggie Macfadyen, name, Maggie Macfadyen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maggie Macfadyen Context triple: [Maggie Macfadyen, name, Maggie Macfadyen]
-
A.
Maggie Macfadyen
chosen
Maggie Macfadyen is the daughter of British actor Matthew Macfadyen and his wife, actress Keeley Hawes.
-
B.
Kristin Scott Thomas
Kristin Scott Thomas is an acclaimed British actress known for her nuanced performances in films such as "The English Patient," "Four Weddings and a Funeral," and "The Horse Whisperer."
-
C.
Joanna Wellick
Joanna Wellick is a calculating and enigmatic character from the television series "Mr. Robot," known for her cold ambition and manipulative influence over her husband Tyrell Wellick.
-
D.
Laura Penn
Laura Penn is known as the spouse of American screenwriter and director Zak Penn.
-
E.
Miranda Raison
Miranda Raison is an English actress known for her work in television, film, and theatre, including roles in "Spooks," "Doctor Who," and various stage productions.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183294984819080b8727a3511a21b |
completed | April 17, 2026, 12:47 a.m. |
Created at: April 10, 2026, 4:56 a.m.