Triple

T2404233
Position Surface form Disambiguated ID Type / Status
Subject Het Hogeland E50238 entity
Predicate containsSettlement P847 FINISHED
Object Winsum E262908 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: Winsum | Statement: [Het Hogeland, containsSettlement, Winsum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Winsum
Context triple: [Het Hogeland, containsSettlement, Winsum]
  • A. Winsum chosen
    Winsum is a historic village and former municipality in the Dutch province of Groningen, known for its old churches, windmills, and picturesque canals.
  • B. Mechernich
    Mechernich is a small town in the Eifel region of North Rhine-Westphalia, Germany, known for its rural landscape and cultural landmarks such as the Bruder Klaus Field Chapel.
  • C. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • D. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • E. Neunkirchen
    Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc8fa151081909bc6be528b29b315 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf403f74819082dc50e31f29b171 completed March 9, 2026, 12:38 p.m.
Created at: March 4, 2026, 7:58 p.m.