Triple
T35081049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisteria Lane |
E1012436
|
entity |
| Predicate | streetNumberingStyle |
P49387
|
FINISHED |
| Object | American suburban |
—
|
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: American suburban | Statement: [Wisteria Lane, streetNumberingStyle, American suburban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetNumberingStyle Context triple: [Wisteria Lane, streetNumberingStyle, American suburban]
-
A.
hasStreetNumberingSystem
chosen
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
-
B.
hasStreetNumberingRole
Indicates that an entity serves a specific function or responsibility related to assigning, managing, or representing street numbers within an addressing system.
-
C.
isNumberedStreet
Indicates that a street is designated primarily by a number (e.g., "1st Street," "42nd Avenue") rather than by a proper name.
-
D.
roadNumberType
Indicates the classification or type category assigned to a road’s identifying number (e.g., highway, route, local road).
-
E.
hasStreetNamingPattern
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given 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_69f76dd32c008190853aef6028f60208 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.