Triple
T17825911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ljusnarsberg Municipality |
E445116
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bergslagen |
—
|
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: Bergslagen | Statement: [Ljusnarsberg Municipality, locatedIn, Bergslagen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bergslagen Context triple: [Ljusnarsberg Municipality, locatedIn, Bergslagen]
-
A.
Bergslagen
chosen
Bergslagen is a historic mining and industrial region in central Sweden known for its rich iron ore deposits and long-standing metallurgical industry.
-
B.
Dalsland
Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
-
C.
Bohuslän
Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
-
D.
Dalarna
Dalarna is a historical province in central Sweden known for its distinct cultural traditions, including unique dialects, folk costumes, and the iconic Dala horse.
-
E.
Uppland
Uppland is a historical province in east-central Sweden that includes parts of the greater Stockholm area and key infrastructure such as Stockholm Arlanda Airport.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48914226c819083edcc78e00b2d42 |
completed | April 19, 2026, 7:49 a.m. |
Created at: April 10, 2026, 10:15 a.m.