Triple
T4036694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oliver Platt |
E83843
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Flatliners |
E357005
|
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: Flatliners | Statement: [Oliver Platt, notableWork, Flatliners]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flatliners Context triple: [Oliver Platt, notableWork, Flatliners]
-
A.
Flatliners
chosen
Flatliners is a 1990 science fiction psychological horror film about medical students who experiment with near-death experiences, directed by Joel Schumacher and starring Kiefer Sutherland, Julia Roberts, and Kevin Bacon.
-
B.
Afterlife
Afterlife is a contemporary novel by Julia Alvarez that explores themes of grief, identity, and immigration through the story of a recently widowed Dominican-American professor.
-
C.
Afterlife
"Afterlife" is a British television drama series starring Andrew Lincoln as a university lecturer who becomes entangled with a troubled medium claiming to communicate with the dead.
-
D.
Afterlife
"Afterlife" is a television film featuring Michael Learned that explores themes of death and what may lie beyond it.
-
E.
The Body
"The Body" is a coming-of-age novella by Stephen King, best known as the basis for the 1986 film "Stand by Me."
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb349e648190b9f227df4cd76fa0 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5564436788190aff89ebfeeed6d9b |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:36 p.m.