Triple
T11774890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regal Riviera Stadium 8 |
E279991
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Regal |
E271791
|
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: Regal | Statement: [Regal Riviera Stadium 8, brand, Regal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Regal Context triple: [Regal Riviera Stadium 8, brand, Regal]
-
A.
Regal
chosen
Regal is a major American movie theater chain known for operating multiplex cinemas across the United States.
-
B.
Noble
Noble is a surname of English origin historically associated with social rank and often borne by families of distinction.
-
C.
Noble
Noble is an unincorporated community and residential area within Abington Township in Montgomery County, Pennsylvania.
-
D.
Royal
Royal is a French surname most prominently associated with politician Ségolène Royal, a leading figure in contemporary French public life.
-
E.
Majesty
Majesty is a formal honorific style used to address or refer to a reigning monarch, typically a king or queen.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a55f415081908eec78cb2c956598 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f090a95a908190a99e579e51cbeb4a |
completed | April 28, 2026, 10:49 a.m. |
Created at: April 8, 2026, 9:41 p.m.