Triple
T22602491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Lavin |
E574864
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Linda Lavin |
—
|
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 Lavin | Statement: [Linda Lavin, name, Linda Lavin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Lavin Context triple: [Linda Lavin, name, Linda Lavin]
-
A.
Linda Lavin
chosen
Linda Lavin is an American actress and singer best known for her title role in the 1970s–80s sitcom "Alice," which earned her multiple Golden Globe Awards and widespread recognition.
-
B.
Alley Mills
Alley Mills is an American actress best known for her role as Norma Arnold, the mother on the classic television series "The Wonder Years."
-
C.
Danielle Kaye
Danielle Kaye is known as the spouse of British film director and music video creator Tony Kaye.
-
D.
Susan Martin
Susan Martin is best known as the longtime wife of acclaimed American actor Burt Lancaster.
-
E.
Candice Bergen
Candice Bergen is an American actress and former fashion model best known for her Emmy-winning role as the sharp-tongued journalist Murphy Brown on the hit television sitcom of the same name.
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1626eb178819096866d03a78f82fc |
completed | April 29, 2026, 1:44 a.m. |
Created at: April 17, 2026, 2:50 p.m.