Triple
T16247888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bel Air–Beverly Crest Community Plan Area |
E394421
|
entity |
| Predicate | planningDocumentType |
P8653
|
FINISHED |
| Object | community plan |
—
|
LITERAL 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: community plan | Statement: [Bel Air–Beverly Crest Community Plan Area, planningDocumentType, community plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: planningDocumentType Context triple: [Bel Air–Beverly Crest Community Plan Area, planningDocumentType, community plan]
-
A.
planningDocument
Indicates that an entity serves as or is associated with a document created for planning or outlining future actions, strategies, or activities.
-
B.
documentationType
Indicates the specific category or kind of documentation associated with or required for an entity or process.
-
C.
draftType
Indicates the specific category or kind of draft associated with an entity or document (e.g., initial, revised, or final draft).
-
D.
planType
chosen
Indicates the specific category or kind of plan associated with an entity, such as its level, structure, or intended use.
-
E.
hasPlanningType
Indicates that an entity is associated with a specific category or type used for planning or scheduling purposes.
- F. None of above.
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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245942460819080897afad0d2fe09 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.