Triple
T9517703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greater Oslo Region |
E229565
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Frogn |
E542133
|
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: Frogn | Statement: [Greater Oslo Region, contains, Frogn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frogn Context triple: [Greater Oslo Region, contains, Frogn]
-
A.
Frogn
chosen
Frogn is a coastal municipality in Viken county, Norway, known for the historic Oscarsborg Fortress in the Oslofjord.
-
B.
Frosta
Frosta is a rural municipality and peninsula in Trøndelag county, Norway, known for its fertile farmland and historical significance as a medieval assembly site.
-
C.
Flen
Flen is a small Swedish town known as the administrative center of Flen Municipality in the province of Södermanland.
-
D.
Flöha
Flöha is a small town in the Free State of Saxony in eastern Germany, situated near Chemnitz and known historically as a local railway and industrial hub.
-
E.
Drongen
Drongen is a district of the Belgian city of Ghent, known as a suburban area in East Flanders.
- 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_69ca84777560819084cddd999badc1aa |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9880417c819097dde277988df36d |
completed | April 1, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a4aeb008190ae5d54367efe2722 |
completed | April 4, 2026, 4:20 p.m. |
Created at: March 30, 2026, 7:59 p.m.