Triple
T17339434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romerike |
E421025
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Gjerdrum |
—
|
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: Gjerdrum | Statement: [Romerike, contains, Gjerdrum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gjerdrum Context triple: [Romerike, contains, Gjerdrum]
-
A.
Gjerdrum
chosen
Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
-
B.
Gjesdal
Gjesdal is a municipality in Rogaland county in southwestern Norway, known for its rural landscapes and proximity to the city of Stavanger.
-
C.
Brårud
Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
-
D.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
E.
Tjørhom
Tjørhom is a small village in southwestern Norway known for its mountainous landscape and proximity to popular skiing and outdoor recreation areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a14ec90819098db2ac0d58a53e1 |
completed | April 19, 2026, 2:12 a.m. |
Created at: April 10, 2026, 5:44 a.m.