Triple
T21819874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Pleasence |
E538696
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Linda Kentwood |
—
|
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: Linda Kentwood | Statement: [Donald Pleasence, spouse, Linda Kentwood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Kentwood Context triple: [Donald Pleasence, spouse, Linda Kentwood]
-
A.
Linda Kentwood
chosen
Linda Kentwood is known primarily for being married to the English actor Donald Pleasence, famed for his roles in film and theatre.
-
B.
Linda Nordley
Linda Nordley is a central female character in the 1953 adventure film "Mogambo," portrayed as a refined Englishwoman whose arrival complicates the romantic and emotional dynamics on an African safari.
-
C.
Linda Wallem
Linda Wallem is an American television writer, producer, and actress best known for co-creating the acclaimed medical dramedy series "Nurse Jackie."
-
D.
Linda Gunderson
Linda Gunderson is a kind-hearted Minnesota bookshop owner who becomes the human protagonist and caretaker of the rare macaw Blu in the animated film "Rio."
-
E.
Linda Gleason
Linda Gleason is known as the wife of American actor and playwright Jason Miller.
- 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_69e0c475038c8190abb9b1a20eb8ff50 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cce0b8081909e20ded72db40304 |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 16, 2026, 6:54 p.m.