Triple

T8338350
Position Surface form Disambiguated ID Type / Status
Subject Styria E195845 entity
Predicate hasCity P316 FINISHED
Object Judenburg
Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
 E752652 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: Judenburg | Statement: [Styria, hasCity, Judenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Judenburg
Context triple: [Styria, hasCity, Judenburg]
  • A. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • B. Köstendorf
    Köstendorf is a small Austrian municipality in the state of Salzburg, known for its rural character and proximity to the city of Salzburg.
  • C. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • D. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • E. Weidenau
    Weidenau is a district of the city of Siegen in North Rhine-Westphalia, Germany.
  • 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: Judenburg
Triple: [Styria, hasCity, Judenburg]
Generated description
Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Judenburg
Target entity description: Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
  • A. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • B. Köstendorf
    Köstendorf is a small Austrian municipality in the state of Salzburg, known for its rural character and proximity to the city of Salzburg.
  • C. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • D. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • E. Weidenau
    Weidenau is a district of the city of Siegen in North Rhine-Westphalia, Germany.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd68e348190a7cb8639a263b50f completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf27cace5c8190b871c632a075cb0a completed April 3, 2026, 2:36 a.m.
NEDg Description generation batch_69cf2a6a91d48190aa7d45b0a010f261 completed April 3, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_69cf2c0aace08190aca839c39e718c52 completed April 3, 2026, 2:55 a.m.
Created at: March 30, 2026, 5:57 p.m.