Triple
T1477986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scanian War |
E30885
|
entity |
| Predicate | involvedTerritory |
P1059
|
FINISHED |
| Object | Bohuslän |
E163444
|
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: Bohuslän | Statement: [Scanian War, involvedTerritory, Bohuslän]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bohuslän Context triple: [Scanian War, involvedTerritory, Bohuslän]
-
A.
Bohuslän
chosen
Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
-
B.
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.
-
C.
Blekinge
Blekinge is a historical province in southern Sweden on the Baltic Sea coast, known for its archipelago, maritime heritage, and strategic location.
-
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.
Västergötland
Västergötland is a historical province in southwestern Sweden known for its varied landscapes, medieval heritage, and important industrial and urban centers.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c605d4c0819088ab06678b2ba6f3 |
completed | March 1, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae26de62d48190849540112614ccce |
completed | March 9, 2026, 1:48 a.m. |
Created at: March 1, 2026, 8:11 p.m.