Triple
T9385605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanda Plaza |
E225895
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Wanda Cinemas |
E225896
|
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: Wanda Cinemas | Statement: [Wanda Plaza, associatedWith, Wanda Cinemas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanda Cinemas Context triple: [Wanda Plaza, associatedWith, Wanda Cinemas]
-
A.
Wanda Cinemas
chosen
Wanda Cinemas is a major Chinese cinema chain known for operating a large network of modern movie theaters across China.
-
B.
Cinemark Theatres
Cinemark Theatres is a major American movie theater chain operating multiplex cinemas across the United States and in several Latin American countries.
-
C.
Regal Cinemas
Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
-
D.
Cineplex Cinemas
Cineplex Cinemas is a major Canadian movie theatre chain offering multiplex cinema experiences with multiple screens, concessions, and modern film presentation technologies.
-
E.
United Cinemas
United Cinemas is a Japanese movie theater chain operating multiplex cinemas in various locations, including major shopping and entertainment complexes.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d142008190840e131e8f1940f9 |
completed | April 1, 2026, 5:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100eb108c8190add5bacfea1f800a |
completed | April 4, 2026, 12:15 p.m. |
Created at: March 30, 2026, 7:44 p.m.