Triple
T14576223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calabasas |
E342057
|
entity |
| Predicate | hasHighIncomeDemographics |
P44558
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Calabasas, hasHighIncomeDemographics, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighIncomeDemographics Context triple: [Calabasas, hasHighIncomeDemographics, true]
-
A.
medianHouseholdIncomeHighRelativeTo
Indicates that the median household income of one entity is significantly higher compared to that of another specified reference entity or benchmark.
-
B.
isAffluentArea
chosen
Indicates that a given area is characterized by high wealth, income levels, or overall economic prosperity.
-
C.
locatedInAffluentArea
Indicates that something is situated within a geographically defined area characterized by high wealth, income, or socioeconomic status.
-
D.
hasHighCostOfLiving
Indicates that the place or context is associated with expenses for goods, services, or daily life that are significantly higher than average.
-
E.
hasHighGDPShareOf
Indicates that a specified portion or sector accounts for a large percentage of an entity’s total Gross Domestic Product (GDP).
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f5ec448190b2ef887fdf7b633e |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.