Triple
T8874080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidney Luft |
E211224
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Lorna Luft |
E61868
|
NE FINISHED |
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: Lorna Luft | Statement: [Sidney Luft, relative, Lorna Luft]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorna Luft Context triple: [Sidney Luft, relative, Lorna Luft]
-
A.
Lorna Luft
chosen
Lorna Luft is an American singer, actress, and author, best known for her work on stage and screen and for being part of the legendary Garland entertainment family.
-
B.
Lorna Patterson
Lorna Patterson is an American actress best known for her comedic role as the singing stewardess in the classic parody film "Airplane!"
-
C.
Lorraine Ashbourne
Lorraine Ashbourne is an English actress known for her extensive work in television, film, and theatre, including roles in series such as "The Bill," "Jericho," and "Bridgerton."
-
D.
Lorraine Broughton
Lorraine Broughton is a highly skilled, stylish MI6 spy and lethal combatant who serves as the protagonist of the action thriller film "Atomic Blonde."
-
E.
Lorna Crozier
Lorna Crozier is an acclaimed Canadian poet and educator known for her lyrical explorations of memory, landscape, and the human condition.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc614451d081908804430a72d00edf |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0772ba2808190b8b7948a09b8dee5 |
completed | April 4, 2026, 2:27 a.m. |
Created at: March 30, 2026, 6:52 p.m.