Triple

T9745843
Position Surface form Disambiguated ID Type / Status
Subject Main River region E236304 entity
Predicate containsCity P294 FINISHED
Object Seligenstadt E446520 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: Seligenstadt | Statement: [Main River region, containsCity, Seligenstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seligenstadt
Context triple: [Main River region, containsCity, Seligenstadt]
  • 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. Rudolstadt
    Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
  • C. Augustdorf
    Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
  • D. Jüterbog
    Jüterbog is a historic town in the German state of Brandenburg, known for its medieval architecture and long-standing cultural heritage.
  • E. 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.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f65ad788190b68d731b6f516d93 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d354af200881909b08ab9b71d0d53f completed April 6, 2026, 6:37 a.m.
Created at: March 30, 2026, 8:23 p.m.