Triple
T21963609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grønland |
E542400
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Sørenga |
E562394
|
NE 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: Sørenga | Statement: [Grønland, near, Sørenga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sørenga Context triple: [Grønland, near, Sørenga]
-
A.
Sørenga
chosen
Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
-
B.
Søråa
Søråa is a river located in the Namdalen district of Trøndelag county in central Norway.
-
C.
Sørreisa
Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
-
D.
Solevåg
Solevåg is a village in Sula Municipality in Møre og Romsdal county, Norway, known for its coastal setting near the town of Ålesund.
-
E.
Vangsnes
Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12458e4488190a04f8d3958854b49 |
completed | April 28, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bd3574a7c81909c3695d0efe5ee07 |
completed | May 19, 2026, 3:04 a.m. |
Created at: April 16, 2026, 8:01 p.m.