Triple
T34126550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alværn |
E875294
|
entity |
| Predicate | isWithinCommutingAreaOf |
P174603
|
FINISHED |
| Object | Oslo |
—
|
NE NERFINISHED |
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: Oslo | Statement: [Alværn, isWithinCommutingAreaOf, Oslo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWithinCommutingAreaOf Context triple: [Alværn, isWithinCommutingAreaOf, Oslo]
-
A.
isCommuterRegionFor
Indicates that one region primarily serves as a residential base whose inhabitants regularly travel to another region for work or daily activities.
-
B.
isResidentialAreaForCommutersTo
chosen
Indicates that a residential area primarily houses people who commute to the specified destination for work or other regular activities.
-
C.
isWithinMetroArea
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
-
D.
residesNear
Indicates that one entity lives or is located in close physical proximity to another entity.
-
E.
hasTransportationProximityTo
Indicates that one entity is located near or conveniently accessible to another entity in terms of transportation options or routes.
- 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_69f349aa33848190a2e6c5e4533c8444 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:53 a.m.