Triple

T1652355
Position Surface form Disambiguated ID Type / Status
Subject Göppingen E35718 entity
Predicate hasTwinTown P919 FINISHED
Object Sonneberg
Sonneberg is a town in the German state of Thuringia, historically known for its toy-making industry and museums.
E228673 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: Sonneberg | Statement: [Göppingen, hasTwinTown, Sonneberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sonneberg
Context triple: [Göppingen, hasTwinTown, Sonneberg]
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • C. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • D. Nienburg
    Nienburg is a historic town in Lower Saxony, Germany, known for its medieval architecture and scenic location along the Weser River.
  • E. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • 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: Sonneberg
Triple: [Göppingen, hasTwinTown, Sonneberg]
Generated description
Sonneberg is a town in the German state of Thuringia, historically known for its toy-making industry and museums.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sonneberg
Target entity description: Sonneberg is a town in the German state of Thuringia, historically known for its toy-making industry and museums.
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • C. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • D. Nienburg
    Nienburg is a historic town in Lower Saxony, Germany, known for its medieval architecture and scenic location along the Weser River.
  • E. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a88cb108190a836b972f600c257 completed March 5, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fbcd17c81909e6d3771442f1245 completed March 9, 2026, 1:17 a.m.
NEDg Description generation batch_69ae20cb479c8190853d0d954af16887 completed March 9, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_69ae21614e74819093617a355f0857c8 completed March 9, 2026, 1:24 a.m.
Created at: March 4, 2026, 7:29 p.m.