Triple
T12769322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yas Mall |
E305203
|
entity |
| Predicate | hasTenant |
P3277
|
FINISHED |
| Object |
VOX Cinemas
VOX Cinemas is a major cinema chain in the Middle East known for its modern multiplex theaters and premium movie-going experiences.
|
E110674
|
NE FINISHED |
How this triple was built (4 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: VOX Cinemas | Statement: [Yas Mall, hasTenant, VOX Cinemas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VOX Cinemas Context triple: [Yas Mall, hasTenant, VOX Cinemas]
-
A.
Rave Cinemas
Rave Cinemas is a movie theater chain in the United States that operates multiplex cinemas for mainstream film releases.
-
B.
Reel Cinemas
Reel Cinemas is a popular cinema chain in Dubai known for its modern multiplex theaters and premium movie-going experiences.
-
C.
Regal Cinemas
Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
-
D.
Marcus Theatres
Marcus Theatres is a major American movie theater chain known for operating multiplex cinemas across the Midwest and other regions of the United States.
-
E.
Regal Cinema
Regal Cinema is a historic art deco movie theatre in Mumbai, India, known as one of the city’s earliest and most iconic cinema halls.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: VOX Cinemas Triple: [Yas Mall, hasTenant, VOX Cinemas]
Generated description
VOX Cinemas is a major cinema chain in the Middle East known for its modern multiplex theaters and premium movie-going experiences.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VOX Cinemas Target entity description: VOX Cinemas is a major cinema chain in the Middle East known for its modern multiplex theaters and premium movie-going experiences.
-
A.
Rave Cinemas
Rave Cinemas is a movie theater chain in the United States that operates multiplex cinemas for mainstream film releases.
-
B.
Reel Cinemas
chosen
Reel Cinemas is a popular cinema chain in Dubai known for its modern multiplex theaters and premium movie-going experiences.
-
C.
Regal Cinemas
Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
-
D.
Marcus Theatres
Marcus Theatres is a major American movie theater chain known for operating multiplex cinemas across the Midwest and other regions of the United States.
-
E.
Regal Cinema
Regal Cinema is a historic art deco movie theatre in Mumbai, India, known as one of the city’s earliest and most iconic cinema halls.
- F. None of above.
Provenance (5 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df3b2f88190b37b696400178795 |
completed | April 10, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af4bd22c819091050e5a40a4a96a |
completed | May 3, 2026, 2:13 a.m. |
| NEDg | Description generation | batch_69f6b08df448819080c0a7b0921bcc9f |
completed | May 3, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6b121fdb881909a9a321794a3b8f1 |
completed | May 3, 2026, 2:21 a.m. |
Created at: April 9, 2026, 5:28 p.m.