Triple

T579321
Position Surface form Disambiguated ID Type / Status
Subject Old Gutnish E15023 entity
Predicate spokenIn P2266 FINISHED
Object Gotland E22241 NE FINISHED

How this triple was built (2 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: Gotland | Statement: [Old Gutnish, spokenIn, Gotland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gotland
Context triple: [Old Gutnish, spokenIn, Gotland]
  • A. Gotland chosen
    Gotland is Sweden’s largest island, located in the Baltic Sea and known for its medieval town of Visby, limestone cliffs, and rich Viking-era history.
  • B. Öland
    Öland is Sweden’s second-largest island, known for its unique limestone plains, rich birdlife, and popular summer tourism along the Baltic Sea coast.
  • C. Bornholm
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
  • D. Rügen
    Rügen is Germany’s largest island, known for its chalk cliffs, seaside resorts, and beaches along the Baltic Sea coast.
  • E. Helgoland
    Helgoland is a small German archipelago in the North Sea known for its dramatic red sandstone cliffs, unique wildlife, and historical significance as a strategic naval and cultural site.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b6c358081908f458b9e3e208c0d completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a523853a648190bdf48e8148fa642b completed March 2, 2026, 5:43 a.m.
Created at: March 1, 2026, 7:33 p.m.