Triple

T13113378
Position Surface form Disambiguated ID Type / Status
Subject Selketal E311029 entity
Predicate nearbyTown P3883 FINISHED
Object Falkenstein/Harz E856588 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: Falkenstein/Harz | Statement: [Selketal, nearbyTown, Falkenstein/Harz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Falkenstein/Harz
Context triple: [Selketal, nearbyTown, Falkenstein/Harz]
  • A. Falkenstein/Harz chosen
    Falkenstein/Harz is a small town in the German state of Saxony-Anhalt, known for its historic Falkenstein Castle and its location in the scenic Harz region.
  • B. Herzberg am Harz
    Herzberg am Harz is a small town in Lower Saxony, Germany, located on the southern edge of the Harz Mountains and known for its historic castle and timber-framed architecture.
  • C. Falkenstein (Vogtland)
    Falkenstein (Vogtland) is a small town in the Vogtland region of Saxony, Germany, known for its historic architecture and scenic surroundings.
  • D. Geiseltal region
    The Geiseltal region is a former lignite mining area in Saxony-Anhalt, Germany, now known for its large artificial lake, post-mining landscapes, and paleontological significance.
  • E. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817f8ee8819084078b4bec5e4f18 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27f5c4481909bc323c9d0c83dc9 completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 9:06 p.m.