Triple
T16999909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hampstead and Kilburn |
E412413
|
entity |
| Predicate | hasHighPropertyPrices |
P25941
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hampstead and Kilburn, hasHighPropertyPrices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighPropertyPrices Context triple: [Hampstead and Kilburn, hasHighPropertyPrices, yes]
-
A.
hasHighCostOfLiving
Indicates that the place or context is associated with expenses for goods, services, or daily life that are significantly higher than average.
-
B.
hasHighPropertyValues
chosen
Indicates that the associated entity possesses property values that are above a defined or typical threshold.
-
C.
hasHighRiseBuildings
Indicates that the subject location contains one or more tall, multi-story buildings commonly classified as high-rises.
-
D.
haveHighMarketValue
Indicates that an entity possesses a relatively high monetary worth or price in the marketplace compared to similar entities.
-
E.
locatedInAffluentArea
Indicates that something is situated within a geographically defined area characterized by high wealth, income, or socioeconomic status.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d37cd6248190a7202ae754882640 |
completed | April 18, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.