Triple
T33976426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida Izazaga |
E871153
|
entity |
| Predicate | hasAreaTypeAlongRoute |
P6822
|
FINISHED |
| Object | commercial zones |
—
|
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: commercial zones | Statement: [Avenida Izazaga, hasAreaTypeAlongRoute, commercial zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaTypeAlongRoute Context triple: [Avenida Izazaga, hasAreaTypeAlongRoute, commercial zones]
-
A.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
hasAlongRoute
Indicates that one entity lies on or is situated along the path, course, or route taken by another entity.
-
C.
isTypeOfAreaWithin
Indicates that one area is a specific type or category of area that exists within another, larger area.
-
D.
hasMajorRouteType
Indicates that an entity is associated with a primary classification of transportation route (such as highway, rail line, or other major route type).
-
E.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
- 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 1, 2026, 1:50 a.m.