Triple

T6869198
Position Surface form Disambiguated ID Type / Status
Subject North Limburg E158494 entity
Predicate contains P35 FINISHED
Object Bergen, Limburg E23233 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: Bergen, Limburg | Statement: [North Limburg, contains, Bergen, Limburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergen, Limburg
Context triple: [North Limburg, contains, Bergen, Limburg]
  • A. Limburg (Belgium)
    Limburg (Belgium) is a Dutch-speaking province in northeastern Belgium known for its green landscapes, cycling routes, and historic towns such as Hasselt and Tongeren.
  • B. Limburg (Netherlands) chosen
    Limburg (Netherlands) is a southeastern Dutch province known for its hilly landscape, distinct Limburgish culture and language, and strategic position bordering Belgium and Germany.
  • C. Limburg an der Vesdre
    Limburg an der Vesdre is a historic town in eastern Belgium that once served as the capital of the medieval Duchy of Limburg.
  • D. North Limburg
    North Limburg is a cultural region in the northern part of the Dutch province of Limburg, known for its distinct dialects, rural landscapes, and cross-border ties with Germany.
  • E. Roermond
    Roermond is a historic city in the southeastern Netherlands known for its medieval architecture, prominent churches, and large designer outlet shopping center.
  • 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_69c68831e3648190a643c328122e4d43 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8a916a88190b81551731dff2898 completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c74299ae148190a56c7b1ee8829f40 completed March 28, 2026, 2:53 a.m.
Created at: March 27, 2026, 2:22 p.m.