Triple

T12877784
Position Surface form Disambiguated ID Type / Status
Subject Leipzig metropolitan region E308012 entity
Predicate containsCity P294 FINISHED
Object Weißenfels E252109 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: Weißenfels | Statement: [Leipzig metropolitan region, containsCity, Weißenfels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weißenfels
Context triple: [Leipzig metropolitan region, containsCity, Weißenfels]
  • A. Weißenfels chosen
    Weißenfels is a historic town in the German state of Saxony-Anhalt, known for its baroque architecture and former prominence as a ducal residence and industrial center.
  • B. Rudolstadt
    Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
  • C. Haldensleben
    Haldensleben is a town in the German state of Saxony-Anhalt, known as an administrative and economic center with historical roots dating back to the Middle Ages.
  • D. Wernigerode
    Wernigerode is a picturesque German town in Saxony-Anhalt known for its colorful half-timbered houses, medieval castle, and location on the northern slopes of the Harz Mountains.
  • E. Harzgerode
    Harzgerode is a small historic town in the eastern Harz Mountains of central Germany, known for its mining heritage and surrounding forested landscapes.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e70dc788190850278a40a5a62e4 completed May 9, 2026, 12:23 a.m.
Created at: April 9, 2026, 5:38 p.m.