Triple
T18750791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Daniels |
E458517
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Debbie McGee |
—
|
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: Debbie McGee | Statement: [Paul Daniels, spouse, Debbie McGee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Debbie McGee Context triple: [Paul Daniels, spouse, Debbie McGee]
-
A.
Debbie McGee
chosen
Debbie McGee is an English television and radio presenter and former ballet dancer best known as the longtime assistant and widow of magician Paul Daniels.
-
B.
Dee Carroll
Dee Carroll was an actress who appeared in the classic television anthology series The Twilight Zone, including the episode "A Stop at Willoughby."
-
C.
Sylvia Dee
Sylvia Dee was an American lyricist best known for writing the words to popular mid-20th-century songs, including the hit ballad "Too Young."
-
D.
Debbie Eagan
Debbie Eagan is a central character in the Netflix series "GLOW," portrayed as a former soap opera actress who reinvents herself as a professional wrestler.
-
E.
Frances Dee
Frances Dee was an American film actress of the 1930s and 1940s, known for her poised, refined screen presence in dramas and literary adaptations.
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e579ec71cc8190bb6d3fa6cca6dc8c |
completed | April 20, 2026, 12:57 a.m. |
Created at: April 10, 2026, 11:51 a.m.