Triple
T19643320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholina Lambert |
E471599
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Belle 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: Belle Vista | Statement: [Catholina Lambert, notableWork, Belle Vista]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belle Vista Context triple: [Catholina Lambert, notableWork, Belle Vista]
-
A.
Belle Vista
chosen
Belle Vista is an alternate name for Lambert Castle, a historic 19th-century mansion and museum located in Paterson, New Jersey.
-
B.
Bella Vista
Bella Vista is a small unincorporated community in Northern California’s Shasta County, known for its rural setting near Redding.
-
C.
Bella Vista
Bella Vista is a historic, culturally vibrant neighborhood in South Philadelphia known for its Italian Market and diverse dining scene.
-
D.
Belleview
Belleview is a small city in Marion County, Florida, known as part of the Ocala metropolitan area in north-central Florida.
-
E.
Grandview
Grandview is a city in Texas known for its small-town character and proximity to recreational areas like Meadowmere Park.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641239ca08190a8bb8854f21ab562 |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:44 p.m.