Triple
T18326972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Øyeren |
E439035
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object |
Kjerringholmen
Kjerringholmen is a small Norwegian island located within Lake Øyeren, known for its natural scenery and tranquil surroundings.
|
E1392077
|
NE FINISHED |
How this triple was built (4 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: Kjerringholmen | Statement: [Øyeren, hasIsland, Kjerringholmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kjerringholmen Context triple: [Øyeren, hasIsland, Kjerringholmen]
-
A.
Gressholmen
Gressholmen is a small recreational island near central Oslo, Norway, known for its beaches, nature reserve areas, and former seaplane airport.
-
B.
Røsholmholmen
Røsholmholmen is a small island located in Tyrifjorden, a large lake in southeastern Norway.
-
C.
Hirsholmene
Hirsholmene is a small Danish archipelago and protected nature reserve in the Kattegat, known for its rich birdlife and unspoiled coastal landscapes.
-
D.
Bømlo
Bømlo is a large island and municipality in Vestland county, Norway, known for its rugged coastline, fishing communities, and extensive network of tunnels and bridges connecting it to the mainland.
-
E.
Bjørnø
Bjørnø is a small Danish island known for its tranquil rural landscape and coastal scenery in the South Funen region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kjerringholmen Triple: [Øyeren, hasIsland, Kjerringholmen]
Generated description
Kjerringholmen is a small Norwegian island located within Lake Øyeren, known for its natural scenery and tranquil surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kjerringholmen Target entity description: Kjerringholmen is a small Norwegian island located within Lake Øyeren, known for its natural scenery and tranquil surroundings.
-
A.
Gressholmen
Gressholmen is a small recreational island near central Oslo, Norway, known for its beaches, nature reserve areas, and former seaplane airport.
-
B.
Røsholmholmen
Røsholmholmen is a small island located in Tyrifjorden, a large lake in southeastern Norway.
-
C.
Hirsholmene
Hirsholmene is a small Danish archipelago and protected nature reserve in the Kattegat, known for its rich birdlife and unspoiled coastal landscapes.
-
D.
Bømlo
Bømlo is a large island and municipality in Vestland county, Norway, known for its rugged coastline, fishing communities, and extensive network of tunnels and bridges connecting it to the mainland.
-
E.
Bjørnø
Bjørnø is a small Danish island known for its tranquil rural landscape and coastal scenery in the South Funen region.
- F. None of above. chosen
Provenance (5 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aab3e7c81909b1c0a688707dfd6 |
completed | April 19, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07b4d35f088190875264a509504dc7 |
completed | May 16, 2026, 12:05 a.m. |
| NEDg | Description generation | batch_6a07b5fa3d348190b8c7adb42097b40a |
completed | May 16, 2026, 12:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07b6644d108190b21ac258ffcfba61 |
completed | May 16, 2026, 12:12 a.m. |
Created at: April 10, 2026, 10:36 a.m.