Triple
T20661289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rage |
E507764
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Charlie Decker |
—
|
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: Charlie Decker | Statement: [Rage, hasCharacter, Charlie Decker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlie Decker Context triple: [Rage, hasCharacter, Charlie Decker]
-
A.
Charlie Decker
chosen
Charlie Decker is the troubled teenage protagonist of Stephen King’s early novel "Rage," known for his violent classroom hostage-taking and psychological unraveling.
-
B.
Scott Decker
Scott Decker is a member of the visual effects and animation company Trixter, contributing to its film and media projects.
-
C.
Jack Deerson
Jack Deerson is a cinematographer best known for his work on the 1971 road movie "Two-Lane Blacktop."
-
D.
Michael Dilbeck
Michael Dilbeck is a film producer best known for his work on the comedy movie "Meet Wally Sparks."
-
E.
Alex Datcher
Alex Datcher is an American actress best known for her role as a flight attendant alongside Wesley Snipes in the 1992 action film "Passenger 57."
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f16adc8190b2b9a69586fa7444 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:44 a.m.