Triple
T18838924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bela Vista |
E460738
|
entity |
| Predicate | hasOfficialName |
P66
|
FINISHED |
| Object | Bela Vista |
—
|
NE NERFINISHED |
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: Bela Vista | Statement: [Bela Vista, hasOfficialName, Bela Vista]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bela Vista Context triple: [Bela Vista, hasOfficialName, Bela Vista]
-
A.
Bela Vista
chosen
Bela Vista is a settlement located on the island and municipality of São Vicente in Cape Verde.
-
B.
Bela Vista
Bela Vista is a central São Paulo neighborhood known for its strong Italian heritage, vibrant cultural scene, and numerous restaurants and theaters.
-
C.
Bella Vista
Bella Vista is a historic, culturally vibrant neighborhood in South Philadelphia known for its Italian Market and diverse dining scene.
-
D.
Bella Vista
Bella Vista is a small unincorporated community in Northern California’s Shasta County, known for its rural setting near Redding.
-
E.
Belle Vista
Belle Vista is an alternate name for Lambert Castle, a historic 19th-century mansion and museum located in Paterson, New Jersey.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a9a0a9a48190b19b131f06b6f72f |
completed | April 20, 2026, 4:20 a.m. |
Created at: April 10, 2026, 11:56 a.m.