Triple

T940054
Position Surface form Disambiguated ID Type / Status
Subject Pomerania E20284 entity
Predicate containsCity P294 FINISHED
Object Stralsund
Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
 E181851 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: Stralsund | Statement: [Pomerania, containsCity, Stralsund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stralsund
Context triple: [Pomerania, containsCity, Stralsund]
  • 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. 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.
  • C. Wismar
    Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
  • D. Fredericia
    Fredericia is a Danish coastal town in Jutland known for its historic 17th-century fortress and well-preserved ramparts.
  • E. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • 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: Stralsund
Triple: [Pomerania, containsCity, Stralsund]
Generated description
Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stralsund
Target entity description: Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
  • 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. 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.
  • C. Wismar
    Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
  • D. Fredericia
    Fredericia is a Danish coastal town in Jutland known for its historic 17th-century fortress and well-preserved ramparts.
  • E. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • 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_69a493b0270c81909e6c9ce310f6aa55 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b38b7da08190ac0853655dab678a completed March 1, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad5187234c8190aeaaf8f4b3b055cb completed March 8, 2026, 10:37 a.m.
NEDg Description generation batch_69ad51f2ae4c819098a2496aa85c20fe completed March 8, 2026, 10:39 a.m.
NED2 Entity disambiguation (via description) batch_69ad5249fee88190895828735cd2e1f8 completed March 8, 2026, 10:41 a.m.
Created at: March 1, 2026, 7:40 p.m.