Triple

T7367653
Position Surface form Disambiguated ID Type / Status
Subject Langeoog E169911 entity
Predicate administrativeDistrict P2709 FINISHED
Object Wittmund (district) E159879 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 (district) | Statement: [Langeoog, administrativeDistrict, Wittmund (district)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wittmund (district)
Context triple: [Langeoog, administrativeDistrict, Wittmund (district)]
  • A. Wittmund district chosen
    Wittmund district is a rural administrative district in Lower Saxony, Germany, located on the North Sea coast and encompassing part of the East Frisian region.
  • B. Wittmund
    Wittmund is a small town in Lower Saxony, Germany, known as an administrative center in the East Frisia region.
  • C. Witzenhausen
    Witzenhausen is a small town in northern Hesse, Germany, known for its cherry orchards and agricultural research institutions.
  • D. Warendorf district
    Warendorf district is a rural administrative district in the German state of North Rhine-Westphalia, known for its agricultural landscape and equestrian traditions.
  • E. Bergheim district
    Bergheim district is an urban area of Heidelberg, Germany, known for its mix of residential neighborhoods, commercial spaces, and university facilities including the Bergheim campus.
  • 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_69c68a5ade988190885b7175f63b7534 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f17ea0608190955ac3474f6da7bb completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802bc25908190ad444de63b7526a0 completed March 28, 2026, 4:33 p.m.
Created at: March 27, 2026, 3:06 p.m.