Triple
T15435895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Made in America |
E369760
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jennifer Tilly |
E241896
|
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: Jennifer Tilly | Statement: [Made in America, starring, Jennifer Tilly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Tilly Context triple: [Made in America, starring, Jennifer Tilly]
-
A.
Jennifer Tilly
chosen
Jennifer Tilly is an American actress and poker player known for her distinctive voice and roles in films such as "Bullets Over Broadway" and the "Child's Play" horror franchise.
-
B.
Rebecca Tilly
Rebecca Tilly is a member of the Tilly family and the sister of actress and author Meg Tilly.
-
C.
Amanda Burton
Amanda Burton is a Northern Irish actress best known for starring as forensic pathologist Dr. Sam Ryan in the British crime drama series "Silent Witness."
-
D.
Tamara Tunie
Tamara Tunie is an American actress and director best known for her long-running role as medical examiner Melinda Warner on the television series "Law & Order: Special Victims Unit."
-
E.
Lynne Brimley
Lynne Brimley is best known as the wife of American character actor Wilford Brimley.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edb3ec481908b26164d4470c9bc |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4546959081909f94449c0028ca3e |
completed | May 9, 2026, 2:31 p.m. |
Created at: April 10, 2026, 3:21 a.m.