Triple
T12334878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Roy Mitchell |
E294057
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Cinemark |
E55861
|
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: Cinemark | Statement: [Lee Roy Mitchell, employer, Cinemark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cinemark Context triple: [Lee Roy Mitchell, employer, Cinemark]
-
A.
Cinemark Theatres
chosen
Cinemark Theatres is a major American movie theater chain operating multiplex cinemas across the United States and in several Latin American countries.
-
B.
Regal Cinemas
Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
-
C.
United Cinemas
United Cinemas is a Japanese movie theater chain operating multiplex cinemas in various locations, including major shopping and entertainment complexes.
-
D.
AMC Theatres
AMC Theatres is one of the largest movie theater chains in the world, operating multiplex cinemas across the United States and internationally.
-
E.
Arclight Cinemas
Arclight Cinemas was a premium movie theater chain based in Los Angeles, known for its upscale amenities, reserved seating, and operation of the iconic Cinerama Dome.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f64ad20819080d99e57833b4b51 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b7e7454819099d89db93d0fc1ea |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 8, 2026, 9:53 p.m.