Triple
T26043074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California State Route 2 |
E647748
|
entity |
| Predicate | urbanSegmentType |
P44319
|
FINISHED |
| Object | surface street |
—
|
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: surface street | Statement: [California State Route 2, urbanSegmentType, surface street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanSegmentType Context triple: [California State Route 2, urbanSegmentType, surface street]
-
A.
urbanSegmentName
Indicates the specific name assigned to a segment within an urban area or city layout.
-
B.
urbanSectionType
Indicates the specific category or type of an urban section within a city or built environment (e.g., residential, commercial, industrial).
-
C.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
D.
streetOrAreaType
chosen
Indicates the specific kind or classification of a street or area (such as avenue, boulevard, district, or zone) associated with an entity.
-
E.
cityDistrictType
Indicates the type or classification of a city district within an urban or administrative structure.
- 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_69e77e8c88f08190858c4c81bd2e1b9a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f606588684819087b366450d7c4fa9 |
completed | May 2, 2026, 2:12 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 22, 2026, 9:08 a.m.