Triple

T349979
Position Surface form Disambiguated ID Type / Status
Subject Hamburg E7419 entity
Predicate hasLandBorderWith P224 FINISHED
Object Schleswig-Holstein E45540 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: Schleswig-Holstein | Statement: [Hamburg, hasLandBorderWith, Schleswig-Holstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schleswig-Holstein
Context triple: [Hamburg, hasLandBorderWith, Schleswig-Holstein]
  • A. Schleswig-Holstein chosen
    Schleswig-Holstein is Germany’s northernmost state, known for its North Sea and Baltic Sea coastlines, maritime heritage, and shared border with Denmark.
  • B. Mecklenburg-Vorpommern
    Mecklenburg-Vorpommern is a federal state in northeastern Germany known for its Baltic Sea coastline, numerous lakes, and relatively low population density.
  • 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. Brandenburg
    Brandenburg is a federal state in northeastern Germany that surrounds Berlin and is known for its lakes, forests, and historic Prussian heritage.
  • E. 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.
  • 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: hasLandBorderWith
Context triple: [Hamburg, hasLandBorderWith, Schleswig-Holstein]
  • A. countryBordering
    Indicates that one country shares a land or maritime boundary directly with another country.
  • B. borderedBy chosen
    Indicates that one entity shares a common boundary or edge with another entity.
  • C. continentBorders
    Indicates that one continent shares a land or maritime boundary directly with another continent.
  • D. borderedByContinent
    Indicates that one entity has a land or maritime boundary directly adjacent to the specified continent.
  • E. neighboringCountryBySea
    Indicates that one country is adjacent to another with their territories touching via a shared sea boundary rather than solely by land.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2eb1f028c819098fa6480b4ca5cf0 completed Feb. 28, 2026, 1:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ff465c2c819083d63547a4d0572a completed March 2, 2026, 3:08 a.m.
PD Predicate disambiguation batch_69a2e955d1f88190bd687c46fa7c5469 completed Feb. 28, 2026, 1:10 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.