Triple
T34126449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oslo (maritime border) |
E875290
|
entity |
| Predicate | oppositeMunicipality |
P192729
|
FINISHED |
| Object | Nesodden |
—
|
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: Nesodden | Statement: [Oslo (maritime border), oppositeMunicipality, Nesodden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oppositeMunicipality Context triple: [Oslo (maritime border), oppositeMunicipality, Nesodden]
-
A.
neighbouringMunicipality
Indicates that one municipality directly borders and is adjacent to another municipality.
-
B.
oppositeTownCountry
Indicates that two locations are situated in opposing or contrasting town and country settings, such that one is urban while the other is rural.
-
C.
oppositeTownAcrossBorder
Indicates that one town is located directly across a border from another town, positioned as its opposite counterpart.
-
D.
oppositeCityCountry
Indicates that a city and a country are located on opposite sides of the world or in geographically opposing regions relative to each other.
-
E.
oppositeSettlementProvince
Indicates that two settlements are located in provinces that are considered opposites of each other within a given geographic or administrative framework.
- F. None of above. chosen
Provenance (4 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_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
| PDg | Predicate description generation | batch_69fd28379d2c8190903ba228ee1cc756 |
completed | May 8, 2026, 12:03 a.m. |
Created at: May 1, 2026, 1:53 a.m.