Triple

T5172407
Position Surface form Disambiguated ID Type / Status
Subject Province of Saxony E116715 entity
Predicate capital P234 FINISHED
Object Magdeburg E240455 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: Magdeburg | Statement: [Province of Saxony, capital, Magdeburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magdeburg
Context triple: [Province of Saxony, capital, Magdeburg]
  • A. Magdeburg chosen
    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.
  • B. 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.
  • C. Erfurt
    Erfurt is a historic German city in the state of Thuringia, known for its well-preserved medieval old town and as an important cultural and educational center.
  • D. Cottbus
    Cottbus is a city in eastern Germany known as a regional center for science and technology, including aerospace research.
  • E. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • 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_69bd445ff97c81909a2615cc56235470 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd795252a481908634779f3f656574 completed March 20, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf70c59678819097aed5af25f36b66 completed March 22, 2026, 4:32 a.m.
Created at: March 20, 2026, 1:45 p.m.