Triple
T22093507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rampage (2018 film) |
E545966
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Rampage |
—
|
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: Rampage | Statement: [Rampage (2018 film), title, Rampage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rampage Context triple: [Rampage (2018 film), title, Rampage]
-
A.
Rampage
Rampage is a powerful and sadistic Predacon from Transformers: Beast Wars, known for his near-immortality, immense strength, and unstable, tortured personality.
-
B.
Rampage
Rampage is the official anthropomorphic ram mascot of the NFL’s Los Angeles Rams, known for entertaining fans at games and team events.
-
C.
Rampage
"Rampage" is a significant film and art project by Australian artist and filmmaker George Gittoes that explores gang violence and social decay in inner-city America.
-
D.
Rampage
Rampage is a 1987 crime thriller film about a serial killer and the legal and moral complexities surrounding the death penalty.
-
E.
Rampage
chosen
Rampage is a 2018 science fiction monster film starring Dwayne Johnson, loosely based on the classic arcade video game series of the same name.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e766388190aad1039fe0849771 |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.