Triple

T2404249
Position Surface form Disambiguated ID Type / Status
Subject Het Hogeland E50238 entity
Predicate containsSettlement P847 FINISHED
Object Loppersum E526403 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: Loppersum | Statement: [Het Hogeland, containsSettlement, Loppersum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loppersum
Context triple: [Het Hogeland, containsSettlement, Loppersum]
  • A. Loppersum chosen
    Loppersum is a village and former municipality in the province of Groningen in the Netherlands, known for its historic churches and its location in an area affected by gas-extraction-induced earthquakes.
  • B. Veldhoven
    Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
  • C. Kloosterburen
    Kloosterburen is a small village in the Dutch province of Groningen, known for its historic churches and rural character.
  • D. Zutphen
    Zutphen is a historic city in the eastern Netherlands known for its well-preserved medieval center and location along the river IJssel.
  • E. Hardinxveld-Giessendam
    Hardinxveld-Giessendam is a Dutch town and municipality known for its shipbuilding industry and location along the river Merwede in the province of South Holland.
  • 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_69bfd42f73b88190bb69bffa6a8b9efe completed March 22, 2026, 11:36 a.m.
Created at: March 4, 2026, 7:58 p.m.