Triple

T15438035
Position Surface form Disambiguated ID Type / Status
Subject Meschede E369819 entity
Predicate hasSubdivision P747 FINISHED
Object Wennemen
Wennemen is a village and district of the town of Meschede in North Rhine-Westphalia, Germany.
E1157991 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: Wennemen | Statement: [Meschede, hasSubdivision, Wennemen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wennemen
Context triple: [Meschede, hasSubdivision, Wennemen]
  • A. De Meent
    De Meent is a central shopping center in the Dutch town of Papendrecht, offering a variety of retail stores and services.
  • B. Wieuwerd
    Wieuwerd is a small village in the Dutch province of Friesland, historically noted as the place where the scholar Anna Maria van Schurman spent her final years.
  • C. Waremme
    Waremme is a municipality and town in the Walloon Region of Belgium, known as a local administrative and commercial center in the Province of Liège.
  • D. Essingeleden
    Essingeleden is a major motorway in Stockholm, Sweden, forming part of the city’s ring road and serving as a key route for through traffic around the central islands.
  • E. Menmaatre
    Menmaatre was the throne name of the ancient Egyptian pharaoh Seti I of the Nineteenth Dynasty.
  • 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: Wennemen
Triple: [Meschede, hasSubdivision, Wennemen]
Generated description
Wennemen is a village and district of the town of Meschede in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wennemen
Target entity description: Wennemen is a village and district of the town of Meschede in North Rhine-Westphalia, Germany.
  • A. De Meent
    De Meent is a central shopping center in the Dutch town of Papendrecht, offering a variety of retail stores and services.
  • B. Wieuwerd
    Wieuwerd is a small village in the Dutch province of Friesland, historically noted as the place where the scholar Anna Maria van Schurman spent her final years.
  • C. Waremme
    Waremme is a municipality and town in the Walloon Region of Belgium, known as a local administrative and commercial center in the Province of Liège.
  • D. Essingeleden
    Essingeleden is a major motorway in Stockholm, Sweden, forming part of the city’s ring road and serving as a key route for through traffic around the central islands.
  • E. Menmaatre
    Menmaatre was the throne name of the ancient Egyptian pharaoh Seti I of the Nineteenth Dynasty.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03edca064819081510bf303271062 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21a7d44481909a26b5cc331a3259 completed May 9, 2026, 11:59 a.m.
NEDg Description generation batch_69ff23348a448190a2a2953a18b29aaf completed May 9, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff240af68c8190af88834d97a42afb completed May 9, 2026, 12:09 p.m.
Created at: April 10, 2026, 3:21 a.m.