Triple
T21703431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bohuslän |
E535711
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Fjällbacka |
—
|
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: Fjällbacka | Statement: [Bohuslän, containsTown, Fjällbacka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fjällbacka Context triple: [Bohuslän, containsTown, Fjällbacka]
-
A.
Fjällbacka
chosen
Fjällbacka is a picturesque coastal village in western Sweden, known for its fishing heritage, granite cliffs, and as the setting of Camilla Läckberg’s crime novels.
-
B.
Kungsbacka
Kungsbacka is a town in southwestern Sweden known for its coastal location, historic wooden center, and role as a commuter hub for nearby Gothenburg.
-
C.
Malmberget
Malmberget is a major iron ore mining town in northern Sweden known for its extensive underground operations and associated subsidence issues.
-
D.
Skarpäng
Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
-
E.
Bydalsfjällen
Bydalsfjällen is a mountain area and ski resort region in central Sweden known for its alpine terrain and outdoor recreational activities.
- 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef9b82901c81909de242c920fbc164 |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 16, 2026, 6:46 p.m.