Triple

T16408757
Position Surface form Disambiguated ID Type / Status
Subject Krefeld E398502 entity
Predicate hasDistrict P459 FINISHED
Object Hüls E192632 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: Hüls | Statement: [Krefeld, hasDistrict, Hüls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hüls
Context triple: [Krefeld, hasDistrict, Hüls]
  • A. Hüls chosen
    Hüls is a district of the German city of Krefeld in North Rhine-Westphalia, known for its historic town center and textile-industry heritage.
  • B. Huldenberg
    Huldenberg is a rural municipality in the Flemish Brabant province of Belgium, known for its hilly landscape, forests, and residential villages near Brussels.
  • C. Zwanenburg
    Zwanenburg is a village in North Holland, Netherlands, situated near Amsterdam and known as a suburban residential community within the Haarlemmermeer municipality.
  • D. Winschoten
    Winschoten is a town in the northeast of the Netherlands known historically as a regional trade center and for its traditional windmills and Jewish heritage.
  • E. Tienhoven
    Tienhoven is a small village in the Dutch province of Utrecht, known for its rural landscape and location within the municipality of Stichtse Vecht.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32870e44c8190aae7bc6e6022ceb7 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c64a05c8190a59e800ce2318052 completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:09 a.m.