Triple

T11498347
Position Surface form Disambiguated ID Type / Status
Subject Næstved E272601 entity
Predicate hasNearbyHarbor P42191 FINISHED
Object Karrebæksminde
Karrebæksminde is a small Danish coastal village and popular seaside resort known for its beaches, marina, and fishing community near Næstved on the island of Zealand.
E929227 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: Karrebæksminde | Statement: [Næstved, hasNearbyHarbor, Karrebæksminde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karrebæksminde
Context triple: [Næstved, hasNearbyHarbor, Karrebæksminde]
  • A. Tranekær
    Tranekær is a historic village on the Danish island of Langeland, known for its castle and scenic rural surroundings.
  • B. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • C. Bragernes
    Bragernes is a historic former town and district that now forms the northern part of the city of Drammen in Norway.
  • D. Nakskov
    Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
  • E. Frederiksø
    Frederiksø is a small Danish island in the Baltic Sea that, together with Christiansø, forms part of the Ertholmene archipelago known for its historic fortifications and remote setting.
  • 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: Karrebæksminde
Triple: [Næstved, hasNearbyHarbor, Karrebæksminde]
Generated description
Karrebæksminde is a small Danish coastal village and popular seaside resort known for its beaches, marina, and fishing community near Næstved on the island of Zealand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Karrebæksminde
Target entity description: Karrebæksminde is a small Danish coastal village and popular seaside resort known for its beaches, marina, and fishing community near Næstved on the island of Zealand.
  • A. Tranekær
    Tranekær is a historic village on the Danish island of Langeland, known for its castle and scenic rural surroundings.
  • B. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • C. Bragernes
    Bragernes is a historic former town and district that now forms the northern part of the city of Drammen in Norway.
  • D. Nakskov
    Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
  • E. Frederiksø
    Frederiksø is a small Danish island in the Baltic Sea that, together with Christiansø, forms part of the Ertholmene archipelago known for its historic fortifications and remote setting.
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85de27db081909ccdb4ab0ef75bdb completed April 10, 2026, 2:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69e604aa9e3c8190ad86e4d05a67c8ac completed April 20, 2026, 10:49 a.m.
NEDg Description generation batch_69e610a6de0c8190aabda7ef7b7063a6 completed April 20, 2026, 11:40 a.m.
NED2 Entity disambiguation (via description) batch_69e61853a3b48190b0d132761e9be69c completed April 20, 2026, 12:13 p.m.
Created at: April 8, 2026, 9:36 p.m.