Triple
T22467416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen Brody |
E555390
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Lorraine Gary |
—
|
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: Lorraine Gary | Statement: [Ellen Brody, portrayedBy, Lorraine Gary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorraine Gary Context triple: [Ellen Brody, portrayedBy, Lorraine Gary]
-
A.
Lorraine Gary
chosen
Lorraine Gary is an American actress best known for playing Ellen Brody in the Jaws film series.
-
B.
Lorraine Toussaint
Lorraine Toussaint is a Trinidadian-American actress known for her powerful performances in film and television, including acclaimed roles in projects like "Orange Is the New Black" and numerous independent dramas.
-
C.
Gena Lee Nolin
Gena Lee Nolin is an American actress and model best known for her role as Neely Capshaw on the television series Baywatch.
-
D.
Kathlyn Williams
Kathlyn Williams was a pioneering American silent film actress best known for her work in early adventure serials and melodramas.
-
E.
Linda Rambis
Linda Rambis is an American basketball executive and longtime Los Angeles Lakers executive director of special projects, known for her influential behind-the-scenes role in the organization.
- 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b84e4a88190b6fbfdbd754ba1c5 |
completed | April 29, 2026, 1:14 a.m. |
Created at: April 16, 2026, 8:48 p.m.