Triple

T783555
Position Surface form Disambiguated ID Type / Status
Subject House of Saxe-Coburg and Gotha E16551 entity
Predicate ducalSeat P10501 FINISHED
Object Gotha
Gotha is a historic German city in Thuringia known for its former ducal court, cultural heritage, and role as a residence of various German noble houses.
E258439 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: Gotha | Statement: [House of Saxe-Coburg and Gotha, ducalSeat, Gotha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gotha
Context triple: [House of Saxe-Coburg and Gotha, ducalSeat, Gotha]
  • A. Eisenach
    Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
  • B. Jena
    Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
  • C. Coburg
    Coburg is a historic town in northern Bavaria, Germany, known for its well-preserved medieval architecture and its former role as the seat of the Duchy of Saxe-Coburg and Gotha.
  • D. Oranienburg
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • E. Ansbach
    Ansbach is a historic town in the German state of Bavaria, known as the former residence of the Margraves of Brandenburg-Ansbach.
  • 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: Gotha
Triple: [House of Saxe-Coburg and Gotha, ducalSeat, Gotha]
Generated description
Gotha is a historic German city in Thuringia known for its former ducal court, cultural heritage, and role as a residence of various German noble houses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gotha
Target entity description: Gotha is a historic German city in Thuringia known for its former ducal court, cultural heritage, and role as a residence of various German noble houses.
  • A. Eisenach
    Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
  • B. Jena
    Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
  • C. Coburg
    Coburg is a historic town in northern Bavaria, Germany, known for its well-preserved medieval architecture and its former role as the seat of the Duchy of Saxe-Coburg and Gotha.
  • D. Oranienburg
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • E. Ansbach
    Ansbach is a historic town in the German state of Bavaria, known as the former residence of the Margraves of Brandenburg-Ansbach.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9cecd08190a23c9f65080a4ac7 completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae95c9bbfc81909a02cdca9c859d01 completed March 9, 2026, 9:41 a.m.
NEDg Description generation batch_69ae97ba6cac8190b9a9f48b3f41d8c6 completed March 9, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_69ae9991f438819091c4de282456a138 completed March 9, 2026, 9:57 a.m.
Created at: March 1, 2026, 7:37 p.m.