Triple

T5899031
Position Surface form Disambiguated ID Type / Status
Subject Sachsenhausen E131173 entity
Predicate hasPart P35 FINISHED
Object Sachsenhausen-Nord E131173 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: Sachsenhausen-Nord | Statement: [Sachsenhausen, hasPart, Sachsenhausen-Nord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sachsenhausen-Nord
Context triple: [Sachsenhausen, hasPart, Sachsenhausen-Nord]
  • A. Sachsenhausen chosen
    Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
  • B. Schorfheide
    Schorfheide is a large forested and lake-rich area in Brandenburg, Germany, known for its protected natural landscapes and historical use as a royal and political hunting ground.
  • C. Marzahn-Hellersdorf
    Marzahn-Hellersdorf is a borough in the eastern part of Berlin, Germany, known for its large prefabricated housing estates and extensive green spaces.
  • D. Ludwigsfelde
    Ludwigsfelde is a town in the German state of Brandenburg, located just south of Berlin and known for its industrial history and automotive manufacturing.
  • E. Oranienburger Vorstadt
    Oranienburger Vorstadt is a historic neighborhood in central Berlin, known for its 19th-century urban fabric, cultural sites, and proximity to key political and intellectual centers of the city.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036f7b3f48190a499d43f8ffb2fa7 completed March 22, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b15df86481908b59717b9de63655 completed March 23, 2026, 3:19 a.m.
Created at: March 22, 2026, 3:58 p.m.