Triple

T947219
Position Surface form Disambiguated ID Type / Status
Subject Heidenheim an der Brenz E20438 entity
Predicate hasTwinTown P919 FINISHED
Object Siófok
Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
E132830 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: Siófok | Statement: [Heidenheim an der Brenz, hasTwinTown, Siófok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siófok
Context triple: [Heidenheim an der Brenz, hasTwinTown, Siófok]
  • A. Pécs
    Pécs is a historic cultural and university city in southwestern Hungary, renowned for its Roman and Ottoman heritage and its designation as a European Capital of Culture in 2010.
  • B. Budapest
    Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
  • C. Szeged
    Szeged is a prominent city in southern Hungary known for its university, paprika production, and distinctive Art Nouveau architecture.
  • D. Sopron
    Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
  • E. Pozsony
    Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
  • 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: Siófok
Triple: [Heidenheim an der Brenz, hasTwinTown, Siófok]
Generated description
Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Siófok
Target entity description: Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
  • A. Pécs
    Pécs is a historic cultural and university city in southwestern Hungary, renowned for its Roman and Ottoman heritage and its designation as a European Capital of Culture in 2010.
  • B. Budapest
    Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
  • C. Szeged
    Szeged is a prominent city in southern Hungary known for its university, paprika production, and distinctive Art Nouveau architecture.
  • D. Sopron
    Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
  • E. Pozsony
    Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
  • 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3be19448190a8863fce3d152430 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6611ad508190aac3a6f15a63bbe8 completed March 7, 2026, 5:53 p.m.
NEDg Description generation batch_69ac66a8430c819088544c91725e57bc completed March 7, 2026, 5:55 p.m.
NED2 Entity disambiguation (via description) batch_69ac671d04e48190b839f29511e4cfb5 completed March 7, 2026, 5:57 p.m.
Created at: March 1, 2026, 7:40 p.m.