Triple

T3700480
Position Surface form Disambiguated ID Type / Status
Subject Babelsberg district E78565 entity
Predicate partOf P40 FINISHED
Object city of 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: city of Potsdam | Statement: [Babelsberg district, partOf, city of Potsdam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Potsdam
Context triple: [Babelsberg district, partOf, city of 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. 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.
  • C. Wandlitz
    Wandlitz is a municipality in the German state of Brandenburg, known for its lakes, forests, and proximity to Berlin.
  • D. 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.
  • E. 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.
  • 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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc514eb6c8190b3b74a603c717729 completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c688e0c8190a7e9ea3fe010c361 completed March 14, 2026, 8:29 a.m.
Created at: March 8, 2026, 3:26 p.m.