Triple
T18683513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Långbanshyttan |
E456794
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Värmland |
—
|
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: Värmland | Statement: [Långbanshyttan, locatedIn, Värmland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Värmland Context triple: [Långbanshyttan, locatedIn, Värmland]
-
A.
Värmland County
chosen
Värmland County is a region in west-central Sweden known for its vast forests, lakes, and cultural heritage, with Karlstad as its administrative center.
-
B.
Jämtland region
Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
-
C.
Ångermanland
Ångermanland is a historical province in northern Sweden known for its deep river valleys, forested landscapes, and coastal areas along the Gulf of Bothnia.
-
D.
Dalsland
Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
-
E.
Västmanland
Västmanland is a historic province in central Sweden known for its forests, lakes, and long tradition of mining and metallurgy.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2abf3c8190958c03066b5814af |
completed | April 19, 2026, 10:46 p.m. |
Created at: April 10, 2026, 11:49 a.m.