Triple
T20472802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cory Ellison |
E502233
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Alex Levy |
—
|
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: Alex Levy | Statement: [Cory Ellison, associatedWithCharacter, Alex Levy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alex Levy Context triple: [Cory Ellison, associatedWithCharacter, Alex Levy]
-
A.
Alex Levy
chosen
Alex Levy is a prominent fictional television news anchor and co-host at a major morning show, portrayed by Jennifer Aniston in the drama series "The Morning Show."
-
B.
Jonathan Levy
Jonathan Levy is a central character in the 2021 television miniseries "Scenes from a Marriage," serving as one half of the story’s intensely examined romantic relationship.
-
C.
Michael Levy
Michael Levy is a film producer known for his work on the action-crime drama movie "Waist Deep."
-
D.
Matthew Levy
Matthew Levy is an actor known for his role in the television sitcom "Sons of Tucson."
-
E.
Sam Levy
Sam Levy is an American cinematographer best known for his frequent collaborations with director Noah Baumbach and his work on acclaimed independent films.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69962d810819091bb13fe73250e24 |
completed | April 20, 2026, 9:23 p.m. |
Created at: April 16, 2026, 11:33 a.m.