Triple

T1862391
Position Surface form Disambiguated ID Type / Status
Subject Ems E34843 entity
Predicate region P40 FINISHED
Object Emsland E47544 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: Emsland | Statement: [Ems, region, Emsland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emsland
Context triple: [Ems, region, Emsland]
  • A. Emsland chosen
    Emsland is a rural region in western Germany known for its agriculture, peatlands, and location along the River Ems near the Dutch border.
  • B. Münsterland
    Münsterland is a rural region in northwestern Germany known for its historic castles, cycling routes, and traditional Westphalian culture.
  • C. Uckermark
    Uckermark is a rural historical region in northeastern Germany, known for its lakes, forests, and low population density, located primarily in the state of Brandenburg.
  • D. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • E. District of Vechta
    The District of Vechta is a rural administrative district in Lower Saxony, Germany, known for its agriculture, Catholic traditions, and growing economy within the Oldenburg Münsterland 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb09e714881909cef0f7e77b5b3b9 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaddc9188190bd49d6605fd0e812 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:34 p.m.