Triple
T7541544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gästrikland |
E178285
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Ockelbo |
E176292
|
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: Ockelbo | Statement: [Gästrikland, hasTown, Ockelbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ockelbo Context triple: [Gästrikland, hasTown, Ockelbo]
-
A.
Korsholm
Korsholm is a coastal municipality in western Finland, known for its largely Swedish-speaking population and proximity to the city of Vaasa in the Ostrobothnia region.
-
B.
Rudkøbing
Rudkøbing is a small historic town on the Danish island of Langeland, known for its well-preserved old streets and as the birthplace of physicist Hans Christian Ørsted.
-
C.
Ockelbo Municipality
chosen
Ockelbo Municipality is a rural municipality in Gävleborg County, Sweden, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Lysekil
Lysekil is a coastal town in western Sweden known for its picturesque archipelago, fishing heritage, and popular seaside tourism.
-
E.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8750f80819088ddfb7a5580b5df |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8614c958081908021a0341dc29725 |
completed | March 28, 2026, 11:16 p.m. |
Created at: March 27, 2026, 3:48 p.m.