Triple

T14355878
Position Surface form Disambiguated ID Type / Status
Subject Heiliger See E355969 entity
Predicate locatedIn P40 FINISHED
Object Potsdam E13693 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: Potsdam | Statement: [Heiliger See, locatedIn, Potsdam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Potsdam
Context triple: [Heiliger See, locatedIn, Potsdam]
  • A. Potsdam chosen
    Potsdam is a historic German city near Berlin, known for its palaces, parks, and role in major 20th-century diplomatic events.
  • B. Neustrelitz
    Neustrelitz is a town in northeastern Germany known for hosting a key research center of the German Aerospace Center (DLR), particularly focused on satellite data and space-related technologies.
  • C. Brandenburg an der Havel
    Brandenburg an der Havel is a historic town in eastern Germany, considered one of the cradles of the state of Brandenburg and known for its medieval architecture and waterways.
  • D. Ribnitz-Damgarten
    Ribnitz-Damgarten is a small town in northeastern Germany known as the “Bernsteinstadt” (Amber Town) for its long tradition of amber processing and its location near the Baltic Sea.
  • E. Spandau
    Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f519bf881908615f4d47e0f77aa completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c3d20688190973e37ca38b4afe0 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:15 a.m.