Triple

T133365
Position Surface form Disambiguated ID Type / Status
Subject Baltic Sea E2697 entity
Predicate majorPort P528 FINISHED
Object Lübeck
Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
 E56916 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: Lübeck | Statement: [Baltic Sea, majorPort, Lübeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lübeck
Context triple: [Baltic Sea, majorPort, Lübeck]
  • A. Rostock
    Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
  • B. Hamburg
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • C. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • D. Dresden
    Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
  • E. Osnabrück
    Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
  • 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: Lübeck
Triple: [Baltic Sea, majorPort, Lübeck]
Generated description
Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lübeck
Target entity description: Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
  • A. Rostock
    Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
  • B. Hamburg
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • C. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • D. Dresden
    Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
  • E. Osnabrück
    Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
  • 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a25788b2688190a45b39447f702551 completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a44cb1bfe48190b8b7523b95d4a099 completed March 1, 2026, 2:26 p.m.
NEDg Description generation batch_69a44d42f6548190ba83a589c46be961 completed March 1, 2026, 2:29 p.m.
NED2 Entity disambiguation (via description) batch_69a44d93a1d881908c1ac2685b7ffc6c completed March 1, 2026, 2:30 p.m.
Created at: Feb. 28, 2026, 2:30 a.m.