Triple
T11515076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ScreenX |
E273011
|
entity |
| Predicate | introducedBy |
P513
|
FINISHED |
| Object | CJ CGV |
E273010
|
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: CJ CGV | Statement: [ScreenX, introducedBy, CJ CGV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CJ CGV Context triple: [ScreenX, introducedBy, CJ CGV]
-
A.
CJ CGV (through CJ 4DPLEX)
chosen
CJ CGV, through its subsidiary CJ 4DPLEX, is a South Korean cinema company known for pioneering immersive 4DX movie theater technology worldwide.
-
B.
Wanda Cinemas
Wanda Cinemas is a major Chinese cinema chain known for operating a large network of modern movie theaters across China.
-
C.
Multikino
Multikino is a major Polish multiplex cinema chain operating modern movie theaters across numerous cities in Poland and parts of Europe.
-
D.
Cineworld cinema
Cineworld cinema is a major UK multiplex cinema chain offering mainstream film screenings and entertainment facilities.
-
E.
Cinema City
Cinema City is a European cinema chain brand operated by Cineworld Group, known for its multiplex movie theaters across several countries.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d86db8bf9c8190820c289e6b0c3873 |
completed | April 10, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6852a23688190a3fe8e5508435661 |
completed | April 20, 2026, 7:57 p.m. |
Created at: April 8, 2026, 9:36 p.m.