Triple
T17544176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cousins |
E427281
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Sean Young |
—
|
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: Sean Young | Statement: [Cousins, starring, Sean Young]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sean Young Context triple: [Cousins, starring, Sean Young]
-
A.
Sean Young
chosen
Sean Young is an American actress best known for her roles in 1980s films such as "Blade Runner," "Dune," and "No Way Out."
-
B.
Susan Dey
Susan Dey is an American actress best known for her breakout role as Laurie Partridge on the 1970s television sitcom "The Partridge Family" and later as a lead on the legal drama "L.A. Law."
-
C.
Andie MacDowell
Andie MacDowell is an American actress and former fashion model best known for her roles in romantic comedies such as "Groundhog Day" and "Four Weddings and a Funeral."
-
D.
Lynne Brimley
Lynne Brimley is best known as the wife of American character actor Wilford Brimley.
-
E.
Leslie Bega
Leslie Bega is an American actress best known for her roles on television series such as "Head of the Class" and "The Sopranos."
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4545fe29c8190a586c75419fa14ea |
completed | April 19, 2026, 4:04 a.m. |
Created at: April 10, 2026, 5:49 a.m.