Triple
T9975731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hudiksvall Municipality |
E196321
|
entity |
| Predicate | hasUrbanArea |
P316
|
FINISHED |
| Object | Delsbo |
E832703
|
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: Delsbo | Statement: [Hudiksvall Municipality, hasUrbanArea, Delsbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Delsbo Context triple: [Hudiksvall Municipality, hasUrbanArea, Delsbo]
-
A.
Delsbo
chosen
Delsbo is a locality in Hälsingland, Sweden, known for its traditional folk music heritage and annual Delsbo Folk Music Festival.
-
B.
Nannfeldt
Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
-
C.
Hedesunda
Hedesunda is a small locality in east-central Sweden known for its rural character and proximity to forests, lakes, and the Dalälven River.
-
D.
Blokhus
Blokhus is a Danish seaside resort town known for its wide sandy beaches, coastal dunes, and tourism along the North Sea.
-
E.
Tyvholm
Tyvholm is one of the small Danish islands that form part of the Hirsholmene archipelago in the Kattegat.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb84b47308190aa2f94fa7320cdc3 |
completed | April 2, 2026, 12:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257c9f6cc81908256dc1e8d6c3fea |
completed | April 5, 2026, 12:38 p.m. |
Created at: March 30, 2026, 8:48 p.m.