Triple

T1358865
Position Surface form Disambiguated ID Type / Status
Subject Count of Vechta E29051 entity
Predicate presentDayFederalState P6536 FINISHED
Object Lower Saxony E4364 NE FINISHED

How this triple was built (3 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: Lower Saxony | Statement: [Count of Vechta, presentDayFederalState, Lower Saxony]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lower Saxony
Context triple: [Count of Vechta, presentDayFederalState, Lower Saxony]
  • A. Lower Saxony chosen
    Lower Saxony is a large federal state in northwestern Germany known for its diverse landscapes, strong industrial base, and historic cities such as Hanover and Göttingen.
  • B. Saxony-Anhalt
    Saxony-Anhalt is a federal state in central Germany known for its rich cultural heritage, including numerous UNESCO World Heritage Sites such as the Bauhaus in Dessau and the historic towns of Quedlinburg and Wittenberg.
  • C. Thuringia
    Thuringia is a federal state in central Germany known for its forested landscapes, historic cities like Weimar and Erfurt, and its rich cultural and intellectual heritage.
  • D. Mecklenburg-Vorpommern
    Mecklenburg-Vorpommern is a federal state in northeastern Germany known for its Baltic Sea coastline, numerous lakes, and relatively low population density.
  • E. North Rhine-Westphalia
    North Rhine-Westphalia is Germany’s most populous federal state, known for its major industrial regions, cultural hubs like Cologne and Düsseldorf, and numerous universities and research institutions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: presentDayFederalState
Context triple: [Count of Vechta, presentDayFederalState, Lower Saxony]
  • A. modernStatesInRegion chosen
    Indicates that a state is a contemporary/modern political entity located within a specified geographic region.
  • B. primaryStates
    Indicates that certain states or conditions are the main or most fundamental ones within a given context or system.
  • C. states
    Indicates that an entity formally declares, expresses, or asserts a fact, opinion, or condition about another entity or situation.
  • D. stateOrTerritory
    Indicates that one entity is a state or territory that is politically or administratively associated with another entity.
  • E. stateName
    Indicates that an entity is identified by or associated with a particular state’s name.
  • F. None of above.

Provenance (4 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_69a498d77abc8190913bf57e5f51d2c4 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c290db288190910fcfa17e902663 completed March 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69afc61b715c81908bb4849b03617d85 completed March 10, 2026, 7:19 a.m.
PD Predicate disambiguation batch_69a4bef7700c819099b294e8d9320e70 completed March 1, 2026, 10:34 p.m.
Created at: March 1, 2026, 7:56 p.m.