Triple

T3924978
Position Surface form Disambiguated ID Type / Status
Subject Kölner Haie E93252 entity
Predicate basedInFederalState P13794 FINISHED
Object North Rhine-Westphalia E20221 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: North Rhine-Westphalia | Statement: [Kölner Haie, basedInFederalState, North Rhine-Westphalia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: North Rhine-Westphalia
Context triple: [Kölner Haie, basedInFederalState, North Rhine-Westphalia]
  • A. North Rhine-Westphalia chosen
    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.
  • B. Rhineland-Palatinate
    Rhineland-Palatinate is a federal state in western Germany known for its wine-growing regions along the Rhine and Moselle rivers and its historic cities such as Mainz and Trier.
  • C. Lower Saxony
    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.
  • D. South Westphalia
    South Westphalia is a region in western Germany known for its mixed industrial and rural character, encompassing parts of North Rhine-Westphalia including the Arnsberg area.
  • E. Baden-Württemberg
    Baden-Württemberg is a federal state in southwest Germany known for its strong economy, automotive industry, and cities like Stuttgart, Heidelberg, and Freiburg.
  • 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: basedInFederalState
Context triple: [Kölner Haie, basedInFederalState, North Rhine-Westphalia]
  • A. locatedInFederalEntity chosen
    Indicates that one entity is geographically or administratively situated within the jurisdiction or boundaries of a specified federal entity.
  • B. stateOrTerritory
    Indicates that one entity is a state or territory that is politically or administratively associated with another entity.
  • C. stateFederation
    Indicates that a state is a member of, or participates in, a larger federal union or federation.
  • D. housedInState
    Indicates that an entity is located or situated within the boundaries of a particular state.
  • E. foundingState
    Indicates that a state or entity played a primary role in establishing or creating another organization, institution, or political entity.
  • 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_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeed7dacdc8190854ebc13db2d24bc completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db5d2fcc8190818b79d873cebcf6 completed March 14, 2026, 10:04 p.m.
PD Predicate disambiguation batch_69aee7609c4081908000ce12ae827c3f completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:23 p.m.