Triple

T9189084
Position Surface form Disambiguated ID Type / Status
Subject Pisz E220534 entity
Predicate germanName P6492 FINISHED
Object Johannisburg
Johannisburg is the former German name for the town of Pisz in northeastern Poland, historically part of East Prussia.
 E784460 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: Johannisburg | Statement: [Pisz, germanName, Johannisburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Johannisburg
Context triple: [Pisz, germanName, Johannisburg]
  • A. Johannisthal
    Johannisthal is a locality in the Berlin borough of Treptow-Köpenick, known historically for Germany’s first airfield and its early aviation activities.
  • B. Lydenburg
    Lydenburg is a historic town in South Africa known for its early gold-mining heritage and proximity to scenic routes and nature reserves in the Mpumalanga province.
  • C. Goldstadt
    Goldstadt is a nickname for the German city of Pforzheim, historically renowned for its jewelry and watchmaking industry.
  • D. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • E. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • 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: Johannisburg
Triple: [Pisz, germanName, Johannisburg]
Generated description
Johannisburg is the former German name for the town of Pisz in northeastern Poland, historically part of East Prussia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Johannisburg
Target entity description: Johannisburg is the former German name for the town of Pisz in northeastern Poland, historically part of East Prussia.
  • A. Johannisthal
    Johannisthal is a locality in the Berlin borough of Treptow-Köpenick, known historically for Germany’s first airfield and its early aviation activities.
  • B. Lydenburg
    Lydenburg is a historic town in South Africa known for its early gold-mining heritage and proximity to scenic routes and nature reserves in the Mpumalanga province.
  • C. Goldstadt
    Goldstadt is a nickname for the German city of Pforzheim, historically renowned for its jewelry and watchmaking industry.
  • D. Neustadt
    Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
  • E. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • 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_69ca83e6d77c81909862b7afef56b1bf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccc31d91d48190b8b8874e09c84404 completed April 1, 2026, 7:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c226bc881909609da0bfbd4748e completed April 4, 2026, 12:32 a.m.
NEDg Description generation batch_69d060881c908190b22d06eaf9f8b192 completed April 4, 2026, 12:51 a.m.
NED2 Entity disambiguation (via description) batch_69d0611e76988190be93d1d3dd8f1ab1 completed April 4, 2026, 12:53 a.m.
Created at: March 30, 2026, 7:24 p.m.