Triple

T7007473
Position Surface form Disambiguated ID Type / Status
Subject Kvitøya E162492 entity
Predicate formerlyKnownAs P65 FINISHED
Object Hvidøen
Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
 E635767 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: Hvidøen | Statement: [Kvitøya, formerlyKnownAs, Hvidøen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hvidøen
Context triple: [Kvitøya, formerlyKnownAs, Hvidøen]
  • A. Langeland
    Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
  • B. Læsø
    Læsø is a Danish island in the Kattegat known for its salt production, distinctive seaweed-roofed houses, and tranquil coastal landscapes.
  • C. Opalsøen
    Opalsøen is a scenic former granite quarry lake on the Danish island of Bornholm, known for its emerald-green water and dramatic rocky surroundings that attract hikers and nature lovers.
  • D. Bornholm
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
  • E. Møn
    Møn is a Danish island in the Baltic Sea known for its dramatic white chalk cliffs, scenic landscapes, and rich prehistoric and cultural heritage.
  • 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: Hvidøen
Triple: [Kvitøya, formerlyKnownAs, Hvidøen]
Generated description
Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hvidøen
Target entity description: Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
  • A. Langeland
    Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
  • B. Læsø
    Læsø is a Danish island in the Kattegat known for its salt production, distinctive seaweed-roofed houses, and tranquil coastal landscapes.
  • C. Opalsøen
    Opalsøen is a scenic former granite quarry lake on the Danish island of Bornholm, known for its emerald-green water and dramatic rocky surroundings that attract hikers and nature lovers.
  • D. Bornholm
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
  • E. Møn
    Møn is a Danish island in the Baltic Sea known for its dramatic white chalk cliffs, scenic landscapes, and rich prehistoric and cultural heritage.
  • 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc35cb848190a839919021efce81 completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a43c3a081909b9150d36ba107f5 completed March 28, 2026, 5:42 a.m.
NEDg Description generation batch_69c76b3c87708190a04c48c41bb9904b completed March 28, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69c76bb8c7788190bf54b805f651e28e completed March 28, 2026, 5:48 a.m.
Created at: March 27, 2026, 2:33 p.m.