Triple

T6834532
Position Surface form Disambiguated ID Type / Status
Subject DESY E157416 entity
Predicate hasSiteIn P5003 FINISHED
Object Zeuthen
Zeuthen is a municipality in Brandenburg, Germany, known for hosting a major campus of the DESY particle physics research center.
 E621151 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: Zeuthen | Statement: [DESY, hasSiteIn, Zeuthen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zeuthen
Context triple: [DESY, hasSiteIn, Zeuthen]
  • A. Friedland
    Friedland is a town in present-day Pravdinsk, Russia, historically notable as the site of the decisive 1807 Napoleonic battle between French and Russian forces.
  • B. Friedland
    Friedland is a municipality in Lower Saxony, Germany, known for its historic border location and post-World War II refugee transit camp.
  • C. Zinnowitz
    Zinnowitz is a seaside resort town on Germany’s Baltic Sea coast, known for its sandy beaches, historic spa architecture, and tourism on the island of Usedom.
  • D. Rüngsdorf
    Rüngsdorf is a residential district in the southern part of Bonn, Germany, known for its scenic location along the Rhine and its affiliation with the Bad Godesberg borough.
  • E. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • 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: Zeuthen
Triple: [DESY, hasSiteIn, Zeuthen]
Generated description
Zeuthen is a municipality in Brandenburg, Germany, known for hosting a major campus of the DESY particle physics research center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zeuthen
Target entity description: Zeuthen is a municipality in Brandenburg, Germany, known for hosting a major campus of the DESY particle physics research center.
  • A. Friedland
    Friedland is a town in present-day Pravdinsk, Russia, historically notable as the site of the decisive 1807 Napoleonic battle between French and Russian forces.
  • B. Friedland
    Friedland is a municipality in Lower Saxony, Germany, known for its historic border location and post-World War II refugee transit camp.
  • C. Zinnowitz
    Zinnowitz is a seaside resort town on Germany’s Baltic Sea coast, known for its sandy beaches, historic spa architecture, and tourism on the island of Usedom.
  • D. Rüngsdorf
    Rüngsdorf is a residential district in the southern part of Bonn, Germany, known for its scenic location along the Rhine and its affiliation with the Bad Godesberg borough.
  • E. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • 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_69c6882c53608190b99aebef079b23bd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d7ca96008190ba79563c2a9a9b0e completed March 27, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723fd50c88190af005fd58ca0aee6 completed March 28, 2026, 12:42 a.m.
NEDg Description generation batch_69c7247806808190ac60c134cec612c8 completed March 28, 2026, 12:44 a.m.
NED2 Entity disambiguation (via description) batch_69c7253b94f081909e7cee870a12af6b completed March 28, 2026, 12:47 a.m.
Created at: March 27, 2026, 2:18 p.m.