Triple

T10450740
Position Surface form Disambiguated ID Type / Status
Subject Berliner Bezirk Spandau E246414 entity
Predicate hasPart P35 FINISHED
Object Haselhorst E444749 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: Haselhorst | Statement: [Berliner Bezirk Spandau, hasPart, Haselhorst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haselhorst
Context triple: [Berliner Bezirk Spandau, hasPart, Haselhorst]
  • A. Haselhorst chosen
    Haselhorst is a residential and industrial locality in the Spandau borough of Berlin, Germany, known for its housing estates and proximity to the River Havel.
  • B. Enkhuizen
    Enkhuizen is a historic port town in the Dutch province of North Holland, known for its maritime heritage and well-preserved old center on the IJsselmeer.
  • C. Stadshagen
    Stadshagen is a residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • D. Haaksbergen
    Haaksbergen is a town in the eastern Netherlands, near the German border, known for its rural surroundings and cross-border ties with neighboring German communities.
  • E. Sassenheim
    Sassenheim is a town in the Dutch province of South Holland, known historically for its bulb-growing industry and location within the Duin- en Bollenstreek (Dune and Bulb Region).
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe0a6a548190a54212912f618e4e completed April 7, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b78e7ec819093e5e631197ed295 completed May 2, 2026, 7:07 p.m.
Created at: April 6, 2026, 12:17 p.m.