Triple

T7398517
Position Surface form Disambiguated ID Type / Status
Subject North Sea coast of Denmark E170685 entity
Predicate contains P35 FINISHED
Object Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
 E666098 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: Rømø | Statement: [North Sea coast of Denmark, contains, Rømø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rømø
Context triple: [North Sea coast of Denmark, contains, Rømø]
  • A. 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.
  • B. Langeland
    Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
  • C. Bornholm
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
  • D. Suðuroy
    Suðuroy is the southernmost of the Faroe Islands, known for its dramatic coastal cliffs, small fishing villages, and relatively remote, rugged landscape.
  • E. Hvidøen
    Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
  • 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: Rømø
Triple: [North Sea coast of Denmark, contains, Rømø]
Generated description
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rømø
Target entity description: Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
  • A. 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.
  • B. Langeland
    Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
  • C. Bornholm
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
  • D. Suðuroy
    Suðuroy is the southernmost of the Faroe Islands, known for its dramatic coastal cliffs, small fishing villages, and relatively remote, rugged landscape.
  • E. Hvidøen
    Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
  • 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f24c1c208190a3d11e816888760d completed March 27, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8343c1b308190b4ba681158b54aba completed March 28, 2026, 8:04 p.m.
NEDg Description generation batch_69c8350e9b748190ae0761ee82d3d94a completed March 28, 2026, 8:07 p.m.
NED2 Entity disambiguation (via description) batch_69c83597d0f0819091a095e8376fd644 completed March 28, 2026, 8:10 p.m.
Created at: March 27, 2026, 3:09 p.m.