Triple

T7318999
Position Surface form Disambiguated ID Type / Status
Subject German Bight E168488 entity
Predicate hasPart P35 FINISHED
Object Borkum E159874 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: Borkum | Statement: [German Bight, hasPart, Borkum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borkum
Context triple: [German Bight, hasPart, Borkum]
  • A. Borkum chosen
    Borkum is a German North Sea island known for its seaside resorts, sandy beaches, and role as the westernmost of the East Frisian Islands.
  • B. Norderney
    Norderney is a popular German North Sea island known for its sandy beaches, seaside resort town, and role as a major tourist destination in Lower Saxony.
  • C. Föhr
    Föhr is a North Frisian island off the coast of Schleswig-Holstein in northern Germany, known for its mild climate, sandy beaches, and traditional Frisian culture.
  • D. Wangerooge
    Wangerooge is a small German North Sea island known for its sandy beaches, tourism, and car-free environment as part of the East Frisian Islands.
  • E. Neuharlingersiel
    Neuharlingersiel is a small coastal resort village on the North Sea in Lower Saxony, Germany, known for its fishing harbor and as a departure point for ferries to the East Frisian Islands.
  • 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_69c68a5251508190ad68df4151cfeb04 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6ef18b7bc81908a9ee405d684f304 completed March 27, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c827651b7c81908f5dca5903183b7b completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 3:02 p.m.