Triple

T2132742
Position Surface form Disambiguated ID Type / Status
Subject Province of West Prussia E46578 entity
Predicate capital P234 FINISHED
Object Marienwerder
Marienwerder is a historic town in former West Prussia, now known as Kwidzyn in Poland, noted for its medieval architecture and Teutonic Order castle.
 E237940 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: Marienwerder | Statement: [Province of West Prussia, capital, Marienwerder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marienwerder
Context triple: [Province of West Prussia, capital, Marienwerder]
  • A. Kolberg
    Kolberg is a historic Baltic Sea port city in present-day Kołobrzeg, Poland, known for its strategic military importance and spa tourism.
  • B. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • C. Emden
    Emden is a historic port city in northwestern Germany known for its maritime industry and location near the North Sea.
  • D. Schwarmstedt
    Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
  • E. Sassnitz
    Sassnitz is a port town on the Baltic Sea coast of Germany, located on the island of Rügen and known as a gateway to nearby national parks and chalk cliffs.
  • 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: Marienwerder
Triple: [Province of West Prussia, capital, Marienwerder]
Generated description
Marienwerder is a historic town in former West Prussia, now known as Kwidzyn in Poland, noted for its medieval architecture and Teutonic Order castle.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marienwerder
Target entity description: Marienwerder is a historic town in former West Prussia, now known as Kwidzyn in Poland, noted for its medieval architecture and Teutonic Order castle.
  • A. Kolberg
    Kolberg is a historic Baltic Sea port city in present-day Kołobrzeg, Poland, known for its strategic military importance and spa tourism.
  • B. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • C. Emden
    Emden is a historic port city in northwestern Germany known for its maritime industry and location near the North Sea.
  • D. Schwarmstedt
    Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
  • E. Sassnitz
    Sassnitz is a port town on the Baltic Sea coast of Germany, located on the island of Rügen and known as a gateway to nearby national parks and chalk cliffs.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbba0c42c8190ab3ce4bbf1531ee1 completed March 7, 2026, 5:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51a82a7c8190bc6737034d01f176 completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae528634608190bf10e3abf5a2c2d9 completed March 9, 2026, 4:54 a.m.
NED2 Entity disambiguation (via description) batch_69ae536431bc8190b9f293d74046cb27 completed March 9, 2026, 4:58 a.m.
Created at: March 4, 2026, 7:44 p.m.