Triple

T12854574
Position Surface form Disambiguated ID Type / Status
Subject Łužica E307414 entity
Predicate hasMajorCity 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: [Łužica, hasMajorCity, Cottbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cottbus
Context triple: [Łužica, hasMajorCity, 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. Hoyerswerda
    Hoyerswerda is a town in eastern Germany’s Saxony region, historically shaped by lignite mining and now known for its proximity to the emerging Lusatian lake landscape.
  • E. 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.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97021df7481909cd42a0f72040aa5 completed April 10, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64e2991c81908f474fe07a6ba10a completed May 8, 2026, 10:34 p.m.
Created at: April 9, 2026, 5:37 p.m.