Triple
T18510113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halloween (2018 film) |
E452315
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Judy Greer |
—
|
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: Judy Greer | Statement: [Halloween (2018 film), stars, Judy Greer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Judy Greer Context triple: [Halloween (2018 film), stars, Judy Greer]
-
A.
Judy Greer
chosen
Judy Greer is an American actress known for her versatile supporting roles in film and television, including appearances in major franchises like the Marvel Cinematic Universe.
-
B.
Caitlin O’Hara
Caitlin O’Hara is a child psychologist and the protagonist of the science fiction thriller novel *A Vision of Fire* by Gillian Anderson and Jeff Rovin.
-
C.
Michaela Watkins
Michaela Watkins is an American actress and comedian known for her work on "Saturday Night Live" and in numerous television comedies and films.
-
D.
Amanda Peet
Amanda Peet is an American actress known for her work in films like "The Whole Nine Yards" and television series such as "Studio 60 on the Sunset Strip" and "Togetherness."
-
E.
Melissa Hudson
Melissa Hudson is known as the daughter of Stanley Hudson, a character from the American television series "The Office."
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e533457e608190988304bf8bc2db1c |
completed | April 19, 2026, 7:55 p.m. |
Created at: April 10, 2026, 11:36 a.m.