Triple
T17727097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glåma |
E442490
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Røros |
E126707
|
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: Røros | Statement: [Glåma, flowsThrough, Røros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Røros Context triple: [Glåma, flowsThrough, Røros]
-
A.
Røros
chosen
Røros is a historic Norwegian mining town and UNESCO World Heritage Site known for its well-preserved wooden buildings and copper mining heritage.
-
B.
Trysil
Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
-
C.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
D.
Røst
Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
-
E.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e3cb708190b47456ad2008a65e |
completed | April 19, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02f82876c481909b6e55a136e45ccc |
completed | May 12, 2026, 9:51 a.m. |
Created at: April 10, 2026, 10:07 a.m.