Triple

T10728836
Position Surface form Disambiguated ID Type / Status
Subject Nordwestmecklenburg E253019 entity
Predicate contains P35 FINISHED
Object Dassow
Dassow is a small town in northern Germany’s Mecklenburg-Vorpommern region, near the Baltic Sea coast and the border with Schleswig-Holstein.
E897608 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: Dassow | Statement: [Nordwestmecklenburg, contains, Dassow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dassow
Context triple: [Nordwestmecklenburg, contains, Dassow]
  • A. Radeberg
    Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
  • B. Heringsdorf
    Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
  • C. Retzow
    Retzow is a small municipality in the Havelland district of the federal state of Brandenburg in northeastern Germany.
  • D. Damsholte
    Damsholte is a small village on the Danish island of Møn, known for its rural charm and historic church.
  • E. Augustdorf
    Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
  • 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: Dassow
Triple: [Nordwestmecklenburg, contains, Dassow]
Generated description
Dassow is a small town in northern Germany’s Mecklenburg-Vorpommern region, near the Baltic Sea coast and the border with Schleswig-Holstein.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dassow
Target entity description: Dassow is a small town in northern Germany’s Mecklenburg-Vorpommern region, near the Baltic Sea coast and the border with Schleswig-Holstein.
  • A. Radeberg
    Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
  • B. Heringsdorf
    Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
  • C. Retzow
    Retzow is a small municipality in the Havelland district of the federal state of Brandenburg in northeastern Germany.
  • D. Damsholte
    Damsholte is a small village on the Danish island of Møn, known for its rural charm and historic church.
  • E. Augustdorf
    Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
  • 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70fc92a18819089cc67afee1c9b96 completed April 9, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69e343ffc428819085599f251b7553e5 completed April 18, 2026, 8:42 a.m.
NEDg Description generation batch_69e34fb556648190909c403f5b7709f2 completed April 18, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_69e358f860f08190bfd10519ff3806aa completed April 18, 2026, 10:12 a.m.
Created at: April 8, 2026, 9:14 p.m.