Triple
T23153152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ReGenesis |
E578371
|
entity |
| Predicate | originalNetwork |
P2594
|
FINISHED |
| Object | Movie Central |
—
|
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: Movie Central | Statement: [ReGenesis, originalNetwork, Movie Central]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Movie Central Context triple: [ReGenesis, originalNetwork, Movie Central]
-
A.
Movie Central
chosen
Movie Central was a Canadian premium television channel that specialized in airing movies and high-profile television series.
-
B.
Cinestate
Cinestate was an American film production company known for producing genre-driven, often violent and politically provocative independent movies.
-
C.
Reel Mall
Reel Mall is a prominent upscale shopping and lifestyle center located in Shanghai’s central Jing’an District.
-
D.
VOX Cinemas
VOX Cinemas is a major cinema chain in the Middle East known for operating multiplex theaters with premium and immersive movie experiences across numerous shopping malls.
-
E.
Reel Cinemas
Reel Cinemas is a popular cinema chain in Dubai known for its modern multiplex theaters and premium movie-going experiences.
- 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efaa1fc81908fb1987dbf732f46 |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:01 p.m.