Triple

T13208509
Position Surface form Disambiguated ID Type / Status
Subject Harz National Park E314425 entity
Predicate nearbyCity P350 FINISHED
Object Braunlage E78293 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: Braunlage | Statement: [Harz National Park, nearbyCity, Braunlage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Braunlage
Context triple: [Harz National Park, nearbyCity, Braunlage]
  • A. Braunlage chosen
    Braunlage is a German town and ski resort in the Harz Mountains, known for its winter sports, hiking opportunities, and scenic natural surroundings.
  • B. Braunshardt
    Braunshardt is a district of the town of Weiterstadt in the state of Hesse, Germany.
  • C. Bleichert
    Bleichert is a German-origin surname most notably associated with individuals such as Dwight "Bucky" Bleichert, a character in James Ellroy’s crime novel "The Black Dahlia."
  • D. Balke
    Balke is a Norwegian surname most notably associated with the 19th-century landscape painter Peder Balke.
  • E. Braunsbedra
    Braunsbedra is a small town in the Saalekreis district of Saxony-Anhalt in central Germany, known for its location in a former lignite mining area now characterized by lakes and recultivated 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9cb7ac819095cff8699993c419 completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f611b11c8190b9f89313eb2b5fab completed May 3, 2026, 7:15 a.m.
Created at: April 9, 2026, 9:17 p.m.