Triple

T18383629
Position Surface form Disambiguated ID Type / Status
Subject Seligenstadt E446520 entity
Predicate hasCityDistrict P2709 FINISHED
Object Seligenstadt (core town) NE NERFINISHED

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: Seligenstadt (core town) | Statement: [Seligenstadt, hasCityDistrict, Seligenstadt (core town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seligenstadt (core town)
Context triple: [Seligenstadt, hasCityDistrict, Seligenstadt (core town)]
  • A. Seligenstadt chosen
    Seligenstadt is a historic town in Hesse, Germany, known for its well-preserved medieval center and its association with the Carolingian scholar Einhard.
  • B. Johanngeorgenstadt
    Johanngeorgenstadt is a historic mining town in Germany’s Ore Mountains known for its rich folk traditions and craftsmanship, especially in woodcarving and Christmas-related arts.
  • C. Rudolstadt
    Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
  • D. 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.
  • E. Langelsheim
    Langelsheim is a small town in Lower Saxony, Germany, situated in the Harz region and known for its scenic surroundings and historical mining heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179da1048190944398e229e7a4c1 completed April 19, 2026, 5:57 p.m.
Created at: April 10, 2026, 10:45 a.m.