Triple
T15549869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karlstad |
E370713
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Värmland County |
E350015
|
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: Värmland County | Statement: [Karlstad, locatedIn, Värmland County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Värmland County Context triple: [Karlstad, locatedIn, Värmland County]
-
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 County
Jämtland County is a large, sparsely populated region in central Sweden known for its mountains, forests, and popular outdoor tourism areas.
-
C.
Västernorrland County
Västernorrland County is a coastal county in northern Sweden known for its forests, rivers, and towns such as Sundsvall and Härnösand.
-
D.
Västerbotten County
Västerbotten County is a large administrative region in northern Sweden known for its vast forests, coastline along the Gulf of Bothnia, and sparsely populated inland areas.
-
E.
Västmanland County
Västmanland County is an administrative region in central Sweden known for its mix of industrial towns, forests, and lakes.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a93121881909d88ca55a39252ac |
completed | April 16, 2026, 2:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf0a12e081908d7d2ae7c9774f94 |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:08 a.m.