Triple

T13291860
Position Surface form Disambiguated ID Type / Status
Subject Mariendorf E316577 entity
Predicate partOf P40 FINISHED
Object Tempelhof-Schöneberg E34860 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: Tempelhof-Schöneberg | Statement: [Mariendorf, partOf, Tempelhof-Schöneberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tempelhof-Schöneberg
Context triple: [Mariendorf, partOf, Tempelhof-Schöneberg]
  • A. Tempelhof-Schöneberg chosen
    Tempelhof-Schöneberg is a borough of Berlin, Germany, known for its mix of historic residential areas, the former Tempelhof Airport, and significant Cold War-era political sites.
  • B. Treptow-Köpenick
    Treptow-Köpenick is Berlin’s largest and greenest borough, known for its extensive forests, lakes, and historic town centers such as Köpenick.
  • C. Neukölln
    Neukölln is a diverse, historically working-class district in southern Berlin known for its vibrant multicultural community, nightlife, and rapidly changing urban landscape.
  • D. Reinickendorf
    Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
  • E. Steglitz-Zehlendorf
    Steglitz-Zehlendorf is a borough in southwestern Berlin known for its affluent residential areas, lakes and forests, and historically significant sites such as the Wannsee Conference villa.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99077a8f48190b1163448a3a978a2 completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f739760f748190ace82b1f3c8ce204 completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:27 p.m.