Triple

T9605314
Position Surface form Disambiguated ID Type / Status
Subject Eiderstedt E231954 entity
Predicate contains P35 FINISHED
Object Tönning E503863 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: Tönning | Statement: [Eiderstedt, contains, Tönning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tönning
Context triple: [Eiderstedt, contains, Tönning]
  • A. Tönning chosen
    Tönning is a historic town in northern Germany’s Schleswig-Holstein region, known for its strategic location on the Eider River and its former role as a fortified port.
  • B. Tullinge
    Tullinge is a suburban locality in the Stockholm region of Sweden, known for its residential areas, natural surroundings, and commuter connections to central Stockholm.
  • C. Widdersberg
    Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
  • D. Wittmund
    Wittmund is a small town in Lower Saxony, Germany, known as an administrative center in the East Frisia region.
  • E. Tynningö
    Tynningö is an island in Sweden’s Stockholm archipelago, known for its summer homes, natural scenery, and proximity to the town of Vaxholm.
  • 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_69ca8484838c8190b2049199d22fef70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a5e4a7c8190830b5ad9762ece46 completed April 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d17939ed4c8190addfb052b762d454 completed April 4, 2026, 8:48 p.m.
Created at: March 30, 2026, 8:08 p.m.