Triple

T2136262
Position Surface form Disambiguated ID Type / Status
Subject Brandenburg E46660 entity
Predicate hasCity P316 FINISHED
Object Cottbus E203175 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: Cottbus | Statement: [Brandenburg, hasCity, Cottbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cottbus
Context triple: [Brandenburg, hasCity, Cottbus]
  • A. Cottbus chosen
    Cottbus is a city in eastern Germany known as a regional center for science and technology, including aerospace research.
  • B. Magdeburg
    Magdeburg is a historic city in central Germany, known for its medieval cathedral, role as a major trading and industrial center, and location on the Elbe River.
  • C. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • D. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbdc4ce8c81908d143d5451681e6a completed March 7, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1eec6df94819099ee129cc6199935 completed March 11, 2026, 10:37 p.m.
Created at: March 4, 2026, 7:44 p.m.