Triple

T8060995
Position Surface form Disambiguated ID Type / Status
Subject Weiterstadt E188118 entity
Predicate hasSubdivision P747 FINISHED
Object Weiterstadt (core town) E188118 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: Weiterstadt (core town) | Statement: [Weiterstadt, hasSubdivision, Weiterstadt (core town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weiterstadt (core town)
Context triple: [Weiterstadt, hasSubdivision, Weiterstadt (core town)]
  • A. Weiterstadt chosen
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • 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. Calenberger Neustadt
    Calenberger Neustadt is a historic inner-city district of Hanover, Germany, known for its mix of residential areas, cultural sites, and proximity to the city center.
  • D. Burkhardtsdorf
    Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
  • E. Korbach
    Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
  • 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_69ca82b2f68881908c50560697e210da completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3fcc61c0819085edc26e75c5f6d5 completed March 31, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63d6484c8190b2fd2c2bef179fc4 completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:26 p.m.