Triple

T2926248
Position Surface form Disambiguated ID Type / Status
Subject Brocken spectre E78851 entity
Predicate hasAlternativeName P39 FINISHED
Object Brocken bow E78851 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: Brocken bow | Statement: [Brocken spectre, hasAlternativeName, Brocken bow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brocken bow
Context triple: [Brocken spectre, hasAlternativeName, Brocken bow]
  • A. Brocken
    Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
  • B. Brocken spectre chosen
    The Brocken spectre is an atmospheric optical phenomenon in which an observer’s magnified shadow appears surrounded by a halo-like glory on clouds or mist, famously associated with eerie legends from Germany’s Harz Mountains.
  • C. Barlow
    Barlow is a surname most notably associated with John Perry Barlow, the American poet, essayist, and co-founder of the Electronic Frontier Foundation.
  • D. Wysokie Skałki
    Wysokie Skałki is the highest peak of the Pieniny range in southern Poland, known for its scenic views and popular hiking trails.
  • E. Tourangelle
    Tourangelle is the French term for a female inhabitant or native of the city of Tours in central France.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad97c1e9c08190bcec80bc3262697a completed March 8, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b08668a204819082b13e6ce62d5728 completed March 10, 2026, 9 p.m.
Created at: March 8, 2026, 2:55 p.m.