Triple

T10629760
Position Surface form Disambiguated ID Type / Status
Subject Möhnesee E250420 entity
Predicate hasPart P35 FINISHED
Object Drüggelte
Drüggelte is a small village in North Rhine-Westphalia, Germany, known for its historic Romanesque church and rural setting near the Möhnesee reservoir.
E875133 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: Drüggelte | Statement: [Möhnesee, hasPart, Drüggelte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drüggelte
Context triple: [Möhnesee, hasPart, Drüggelte]
  • A. Dettenschwang
    Dettenschwang is a village and district of the market town Dießen am Ammersee in the Bavarian region of Germany.
  • B. Gasselte
    Gasselte is a village in the Dutch province of Drenthe, known for its surrounding forests, heathlands, and recreational lakes.
  • C. Hrozný
    Hrozný is a Czech surname most notably borne by Bedřich Hrozný, the linguist who deciphered the Hittite language.
  • D. Nerenstetten
    Nerenstetten is a small rural municipality in the Alb-Donau district of Baden-Württemberg in southern Germany.
  • E. Knuffingen
    Knuffingen is a fictional miniature city featured in Hamburg’s Miniatur Wunderland, known for its detailed urban landscape and automated model railway and traffic systems.
  • 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: Drüggelte
Triple: [Möhnesee, hasPart, Drüggelte]
Generated description
Drüggelte is a small village in North Rhine-Westphalia, Germany, known for its historic Romanesque church and rural setting near the Möhnesee reservoir.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Drüggelte
Target entity description: Drüggelte is a small village in North Rhine-Westphalia, Germany, known for its historic Romanesque church and rural setting near the Möhnesee reservoir.
  • A. Dettenschwang
    Dettenschwang is a village and district of the market town Dießen am Ammersee in the Bavarian region of Germany.
  • B. Gasselte
    Gasselte is a village in the Dutch province of Drenthe, known for its surrounding forests, heathlands, and recreational lakes.
  • C. Hrozný
    Hrozný is a Czech surname most notably borne by Bedřich Hrozný, the linguist who deciphered the Hittite language.
  • D. Nerenstetten
    Nerenstetten is a small rural municipality in the Alb-Donau district of Baden-Württemberg in southern Germany.
  • E. Knuffingen
    Knuffingen is a fictional miniature city featured in Hamburg’s Miniatur Wunderland, known for its detailed urban landscape and automated model railway and traffic systems.
  • 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_69d96babc290819096c0c914d038ba01 completed April 10, 2026, 9:29 p.m.
NEDg Description generation batch_69d96df03c2881909af8501ecf6ac180 completed April 10, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d96f063d588190adcfd56b2b0afccf completed April 10, 2026, 9:43 p.m.
Created at: April 8, 2026, 9 p.m.