Triple

T21094174
Position Surface form Disambiguated ID Type / Status
Subject Wijk bij Duurstede E519716 entity
Predicate hasPart P35 FINISHED
Object Cothen NE NERFINISHED

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: Cothen | Statement: [Wijk bij Duurstede, hasPart, Cothen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cothen
Context triple: [Wijk bij Duurstede, hasPart, Cothen]
  • A. Cothen chosen
    Cothen is a village in the Dutch province of Utrecht that forms part of the municipality of Wijk bij Duurstede.
  • B. Brandenberg
    Brandenberg is a locality within the town of Todtnau in the Black Forest region of Baden-Württemberg, Germany.
  • C. Riemst
    Riemst is a municipality in the Belgian province of Limburg, known for its rural character and location near the borders with the Netherlands and Germany.
  • D. Biebrich
    Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
  • E. Schwedt
    Schwedt is a town in northeastern Germany, located on the Oder River near the Polish border, known for its industrial facilities and cross-border regional ties.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b507dd9081908fb8bfcbef4c8b46 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e709517a18819081ede1d38e2c4391 completed April 21, 2026, 5:21 a.m.
Created at: April 16, 2026, 2:51 p.m.