Triple

T8774596
Position Surface form Disambiguated ID Type / Status
Subject Natur-Park Schöneberger Südgelände E208545 entity
Predicate operator P179 FINISHED
Object Grün Berlin GmbH E323226 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: Grün Berlin GmbH | Statement: [Natur-Park Schöneberger Südgelände, operator, Grün Berlin GmbH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grün Berlin GmbH
Context triple: [Natur-Park Schöneberger Südgelände, operator, Grün Berlin GmbH]
  • A. Grün Berlin GmbH chosen
    Grün Berlin GmbH is a state-owned company responsible for planning, developing, and managing major public parks and open spaces in Berlin.
  • B. Berliner Verkehrsbetriebe
    Berliner Verkehrsbetriebe is Berlin’s main public transport company, operating the city’s extensive network of U-Bahn trains, trams, and buses.
  • C. S-Bahn Berlin GmbH
    S-Bahn Berlin GmbH is the company responsible for operating Berlin’s urban rapid transit S-Bahn rail network.
  • D. Berliner Flughafen-Gesellschaft
    Berliner Flughafen-Gesellschaft was the municipal company responsible for operating Berlin’s airports, notably during the Cold War era.
  • E. Stadtwerke Verkehrsgesellschaft Frankfurt am Main
    Stadtwerke Verkehrsgesellschaft Frankfurt am Main is the municipal public transport company responsible for operating much of the urban transit network in Frankfurt am Main, Germany.
  • 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_69ca835edb4481909b4aafb616dc5eb7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f2ef3288190988bd69e8a02e741 completed March 31, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51c760b48190b2138cd2861b2c61 completed April 3, 2026, 5:36 a.m.
Created at: March 30, 2026, 6:41 p.m.