Triple

T1282110
Position Surface form Disambiguated ID Type / Status
Subject Svalbard E27348 entity
Predicate containsIsland P970 FINISHED
Object Nordaustlandet
Nordaustlandet is the second-largest island in the Svalbard archipelago, known for its extensive ice caps and remote Arctic wilderness.
E27348 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: Nordaustlandet | Statement: [Svalbard, containsIsland, Nordaustlandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordaustlandet
Context triple: [Svalbard, containsIsland, Nordaustlandet]
  • A. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • B. Svalbard
    Svalbard is a remote Arctic archipelago known for its rugged glaciers, polar bear habitat, and role as a center for polar research and environmental monitoring.
  • C. Queen Maud Land
    Queen Maud Land is a region of Antarctica claimed by Norway, known for its vast ice-covered terrain and numerous research stations.
  • D. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • E. Fosen
    Fosen is a peninsula and traditional district in central Norway known for its coastal landscape, wind farms, and location across the Trondheimsfjord from the city of Trondheim.
  • 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: Nordaustlandet
Triple: [Svalbard, containsIsland, Nordaustlandet]
Generated description
Nordaustlandet is the second-largest island in the Svalbard archipelago, known for its extensive ice caps and remote Arctic wilderness.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nordaustlandet
Target entity description: Nordaustlandet is the second-largest island in the Svalbard archipelago, known for its extensive ice caps and remote Arctic wilderness.
  • A. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • B. Svalbard chosen
    Svalbard is a remote Arctic archipelago known for its rugged glaciers, polar bear habitat, and role as a center for polar research and environmental monitoring.
  • C. Queen Maud Land
    Queen Maud Land is a region of Antarctica claimed by Norway, known for its vast ice-covered terrain and numerous research stations.
  • D. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • E. Fosen
    Fosen is a peninsula and traditional district in central Norway known for its coastal landscape, wind farms, and location across the Trondheimsfjord from the city of Trondheim.
  • F. None of above.

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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b317788190a1672b5ee422a049 completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08a3865c819093a6ffd1a8c74e2e completed March 8, 2026, 5:26 a.m.
NEDg Description generation batch_69ad09206e988190ad76f8beaa8f9fe6 completed March 8, 2026, 5:29 a.m.
NED2 Entity disambiguation (via description) batch_69ad0a30bcdc81908090d6a094ece0f4 completed March 8, 2026, 5:33 a.m.
Created at: March 1, 2026, 7:50 p.m.