Triple
T1469839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood Hills |
E27109
|
entity |
| Predicate | realEstateCharacteristic |
P9356
|
FINISHED |
| Object | high property values |
—
|
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: high property values | Statement: [Hollywood Hills, realEstateCharacteristic, high property values]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realEstateCharacteristic Context triple: [Hollywood Hills, realEstateCharacteristic, high property values]
-
A.
realEstateCategory
Indicates the classification of a property into a specific type or category within real estate (e.g., residential, commercial, industrial).
-
B.
neighborhoodCharacteristic
chosen
Indicates that a particular characteristic, feature, or quality is associated with or describes a given neighborhood.
-
C.
architectureProperty
Indicates that a specified architectural characteristic or feature is attributed to, or associated with, an entity.
-
D.
constructionCharacteristic
Indicates a specific structural or material property that characterizes how something is built or constructed.
-
E.
property
Indicates that one entity possesses, is characterized by, or has an attribute or quality associated with another entity.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5d9dd4c8190ba840a9255cd1293 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.