Triple

T6908811
Position Surface form Disambiguated ID Type / Status
Subject Wittmund district E159879 entity
Predicate contains P35 FINISHED
Object Wittmund E631769 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: Wittmund | Statement: [Wittmund district, contains, Wittmund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wittmund
Context triple: [Wittmund district, contains, Wittmund]
  • A. Wittmund chosen
    Wittmund is a small town in Lower Saxony, Germany, known as an administrative center in the East Frisia region.
  • B. Ramstedt
    Ramstedt is a Finnish surname most notably borne by linguist and diplomat Gustaf John Ramstedt, known for his pioneering work in Altaic and Mongolic studies.
  • C. Breckerfeld
    Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
  • D. Drensteinfurt
    Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
  • E. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • 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_69c68839ccb88190b4aa5cc1aca3448f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9be98748190b5cb698e66e3aa42 completed March 27, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769f6340c8190adab3e28cfe67e4a completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:25 p.m.