Triple
T8090035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hirsholmene |
E188833
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Kølpen
Kølpen is one of the small islands in the Hirsholmene archipelago off the northeast coast of Jutland in Denmark.
|
E711361
|
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: Kølpen | Statement: [Hirsholmene, hasPart, Kølpen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kølpen Context triple: [Hirsholmene, hasPart, Kølpen]
-
A.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
B.
Østre Bolæren
Østre Bolæren is an island in the Bolærne archipelago in the Oslofjord, known for its coastal scenery, outdoor recreation, and former military installations.
-
C.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
-
D.
Kvænangen
Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
-
E.
Minskov
Minskov is a supporting character in the French crime drama film "The Beat That My Heart Skipped," involved in the criminal underworld that complicates the protagonist's life.
- 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: Kølpen Triple: [Hirsholmene, hasPart, Kølpen]
Generated description
Kølpen is one of the small islands in the Hirsholmene archipelago off the northeast coast of Jutland in Denmark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kølpen Target entity description: Kølpen is one of the small islands in the Hirsholmene archipelago off the northeast coast of Jutland in Denmark.
-
A.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
B.
Østre Bolæren
Østre Bolæren is an island in the Bolærne archipelago in the Oslofjord, known for its coastal scenery, outdoor recreation, and former military installations.
-
C.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
-
D.
Kvænangen
Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
-
E.
Minskov
Minskov is a supporting character in the French crime drama film "The Beat That My Heart Skipped," involved in the criminal underworld that complicates the protagonist's life.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb421e30e88190b9699b338b69b81c |
completed | March 31, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc640a42648190bc1a3072eb338e22 |
completed | April 1, 2026, 12:17 a.m. |
| NEDg | Description generation | batch_69cc68d9032c8190af6c5ff64fe46aff |
completed | April 1, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc69f6bb308190a95df95d1a67cfec |
completed | April 1, 2026, 12:42 a.m. |
Created at: March 30, 2026, 5:29 p.m.