Triple
T18510112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halloween (2018 film) |
E452315
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Jamie Lee Curtis |
—
|
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: Jamie Lee Curtis | Statement: [Halloween (2018 film), stars, Jamie Lee Curtis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jamie Lee Curtis Context triple: [Halloween (2018 film), stars, Jamie Lee Curtis]
-
A.
Jamie Lee Curtis
chosen
Jamie Lee Curtis is an American actress and author renowned for her versatile film career spanning horror classics like "Halloween" and acclaimed dramatic and comedic roles.
-
B.
Dee Wallace
Dee Wallace is an American actress best known for her role as the mother in the classic science-fiction film "E.T. the Extra-Terrestrial."
-
C.
Heather Langenkamp
Heather Langenkamp is an American actress best known for playing Nancy Thompson, the resourceful heroine of the original A Nightmare on Elm Street horror film and several of its sequels.
-
D.
Kim Roberts
Kim Roberts is a film editor known for her work on the documentary "Waiting for Superman."
-
E.
Jami Gertz
Jami Gertz is an American actress known for her roles in 1980s films and television series, including standout performances in movies like "The Lost Boys" and "Quicksilver."
- 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.