Triple

T8683011
Position Surface form Disambiguated ID Type / Status
Subject Bolnisi E206083 entity
Predicate formerName P65 FINISHED
Object Katharinenfeld
Katharinenfeld was the historical German settler colony that later became the town of Bolnisi in southern Georgia.
 E792127 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: Katharinenfeld | Statement: [Bolnisi, formerName, Katharinenfeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Katharinenfeld
Context triple: [Bolnisi, formerName, Katharinenfeld]
  • A. Wilhelmsruh
    Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
  • B. Lülsfeld
    Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • C. Abensberg
    Abensberg is a historic town in Bavaria, Germany, known for its medieval architecture and its role as a Napoleonic-era battlefield.
  • D. Grafenrheinfeld
    Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
  • E. Karlshagen
    Karlshagen is a seaside resort village on the Baltic coast of northeastern Germany, located on the island of Usedom and known for its sandy beaches and tourism.
  • 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: Katharinenfeld
Triple: [Bolnisi, formerName, Katharinenfeld]
Generated description
Katharinenfeld was the historical German settler colony that later became the town of Bolnisi in southern Georgia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Katharinenfeld
Target entity description: Katharinenfeld was the historical German settler colony that later became the town of Bolnisi in southern Georgia.
  • A. Wilhelmsruh
    Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
  • B. Lülsfeld
    Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • C. Abensberg
    Abensberg is a historic town in Bavaria, Germany, known for its medieval architecture and its role as a Napoleonic-era battlefield.
  • D. Grafenrheinfeld
    Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
  • E. Karlshagen
    Karlshagen is a seaside resort village on the Baltic coast of northeastern Germany, located on the island of Usedom and known for its sandy beaches and tourism.
  • 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_69ca835379688190aa06b9d98e684d58 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4ae9da3c8190866e24970a7aeba3 completed March 31, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c696913c819089f29ec899d4ee61 completed April 4, 2026, 8:06 a.m.
NEDg Description generation batch_69d0c976a0308190ba66990fe0a3f33e completed April 4, 2026, 8:19 a.m.
NED2 Entity disambiguation (via description) batch_69d0ce28aaf48190a1e6b4040353c6b9 completed April 4, 2026, 8:39 a.m.
Created at: March 30, 2026, 6:32 p.m.