Triple

T8375491
Position Surface form Disambiguated ID Type / Status
Subject Central Germany E197565 entity
Predicate containsCity P294 FINISHED
Object Nordhausen E360994 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: Nordhausen | Statement: [Central Germany, containsCity, Nordhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordhausen
Context triple: [Central Germany, containsCity, Nordhausen]
  • A. Nordhausen chosen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • B. Halberstadt
    Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
  • C. Naumburg
    Naumburg is a historic town in the German state of Saxony-Anhalt, known for its medieval cathedral and as the childhood home of philosopher Friedrich Nietzsche.
  • 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. Sondershausen
    Sondershausen is a small town in the German state of Thuringia, known for its historic castle, former role as a princely residence, and long tradition of mining and music.
  • 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_69ca82f56730819080cec5d991c76f4c completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80bf6b8081909b98762b1f900bef completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfab01c58c81909148dacad2dc7667 completed April 3, 2026, 11:56 a.m.
Created at: March 30, 2026, 6:01 p.m.