Triple

T10629749
Position Surface form Disambiguated ID Type / Status
Subject Möhnesee E250420 entity
Predicate hasPart P35 FINISHED
Object Völlinghausen
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
E953996 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: Völlinghausen | Statement: [Möhnesee, hasPart, Völlinghausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Völlinghausen
Context triple: [Möhnesee, hasPart, Völlinghausen]
  • A. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • B. Nennhausen
    Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
  • C. Thannhausen
    Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
  • D. Balzhausen
    Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
  • E. Kühnhausen
    Kühnhausen is a locality in Germany known historically as the place where Nazi education minister Bernhard Rust died.
  • 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: Völlinghausen
Triple: [Möhnesee, hasPart, Völlinghausen]
Generated description
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Völlinghausen
Target entity description: Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
  • A. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • B. Nennhausen
    Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
  • C. Thannhausen
    Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
  • D. Balzhausen
    Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
  • E. Kühnhausen
    Kühnhausen is a locality in Germany known historically as the place where Nazi education minister Bernhard Rust died.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df92f8388190a8bcff96809d8eb4 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f43ee693048190a8c7ecdf8724d3ec completed May 1, 2026, 5:49 a.m.
NEDg Description generation batch_69f448f506a48190a0f1b89ad570fad5 completed May 1, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f44ad185cc8190893cf663cfed6980 completed May 1, 2026, 6:40 a.m.
Created at: April 8, 2026, 9 p.m.