Triple

T8438345
Position Surface form Disambiguated ID Type / Status
Subject Mechernich E199285 entity
Predicate hasDistrict P459 FINISHED
Object Vussem
Vussem is a village in the town of Mechernich in North Rhine-Westphalia, Germany.
 E735449 NE FINISHED

How this triple was built (4 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: Vussem | Statement: [Mechernich, hasDistrict, Vussem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vussem
Context triple: [Mechernich, hasDistrict, Vussem]
  • A. Buizingen
    Buizingen is a village and suburb of Halle in Flemish Brabant, Belgium, known in part for the 2010 train collision that occurred near its railway station.
  • B. Porrentruy
    Porrentruy is a historic town in northwestern Switzerland known for its medieval castle and role as a regional center in the canton of Jura.
  • C. Verviers
    Verviers is a city in eastern Belgium known historically for its textile industry and as a regional center in the province of Liège.
  • D. Devillars
    Devillars is a French surname, a variant spelling of “de Villars,” historically associated with families and places bearing the Villars name in France.
  • E. Esch-sur-Sûre
    Esch-sur-Sûre is a small historic town in northwestern Luxembourg, known for its medieval castle ruins and picturesque setting along a bend of the Sûre River.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Vussem
Triple: [Mechernich, hasDistrict, Vussem]
Generated description
Vussem is a village in the town of Mechernich in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vussem
Target entity description: Vussem is a village in the town of Mechernich in North Rhine-Westphalia, Germany.
  • A. Buizingen
    Buizingen is a village and suburb of Halle in Flemish Brabant, Belgium, known in part for the 2010 train collision that occurred near its railway station.
  • B. Porrentruy
    Porrentruy is a historic town in northwestern Switzerland known for its medieval castle and role as a regional center in the canton of Jura.
  • C. Verviers
    Verviers is a city in eastern Belgium known historically for its textile industry and as a regional center in the province of Liège.
  • D. Devillars
    Devillars is a French surname, a variant spelling of “de Villars,” historically associated with families and places bearing the Villars name in France.
  • E. Esch-sur-Sûre
    Esch-sur-Sûre is a small historic town in northwestern Luxembourg, known for its medieval castle ruins and picturesque setting along a bend of the Sûre River.
  • F. None of above. chosen

Provenance (5 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_69ca8314cd6c8190a6b8c2a1096e18f3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe135657c81908ed8156fbfbef6ec completed March 31, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce399e8efc8190ad6fa8a6cf91797c completed April 2, 2026, 9:40 a.m.
NEDg Description generation batch_69ce3b31397c81908c9ae4d19095b66d completed April 2, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_69ce3bbf0eb481908e48c8b2eada1f16 completed April 2, 2026, 9:49 a.m.
Created at: March 30, 2026, 6:08 p.m.