Triple

T14355926
Position Surface form Disambiguated ID Type / Status
Subject Glashütte Studio E355970 entity
Predicate locatedIn P40 FINISHED
Object Babelsberg E71648 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: Babelsberg | Statement: [Glashütte Studio, locatedIn, Babelsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Babelsberg
Context triple: [Glashütte Studio, locatedIn, Babelsberg]
  • A. Babelsberg Film Studio chosen
    Babelsberg Film Studio is one of the world’s oldest large-scale film studios and a historic center of German and international film production, located in Potsdam.
  • B. Weimar
    Weimar is a historic German city renowned as a center of culture and the arts, associated with figures like Goethe and Schiller and pivotal movements in modern design and architecture.
  • C. Bavaria Filmstadt
    Bavaria Filmstadt is a film-themed visitor attraction and studio tour in Munich where guests can explore sets, props, and behind-the-scenes aspects of movie and television production.
  • D. Lippendorf
    Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
  • E. Falkensee
    Falkensee is a town in the Havelland district of Brandenburg, Germany, situated just west of Berlin and functioning largely as a residential suburb of the capital.
  • 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_69fd4c473fa48190866ab946971e971c completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:15 a.m.