Triple

T20815946
Position Surface form Disambiguated ID Type / Status
Subject Balatonfüred District E512436 entity
Predicate containsSettlement P847 FINISHED
Object Zánka
Zánka is a small Hungarian village on the northern shore of Lake Balaton, known for its youth camp and scenic surroundings.
 E1453064 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: Zánka | Statement: [Balatonfüred District, containsSettlement, Zánka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zánka
Context triple: [Balatonfüred District, containsSettlement, Zánka]
  • A. Noznisky
    Noznisky is a relatively uncommon family surname associated with individuals such as Shirley Marlin Noznisky.
  • B. Koudelka
    Koudelka is a Czech surname most prominently associated with Josef Koudelka, the renowned photographer known for his powerful black-and-white images documenting Roma communities and political upheaval.
  • C. Kája
    Kája is a Czech diminutive form of the given name Karel.
  • D. Zedka
    Zedka is a fellow patient in Paulo Coelho’s novel "Veronika Decides to Die," known for her struggle with depression and her role in challenging Veronika’s understanding of madness and freedom.
  • E. Znamianka
    Znamianka is a city in central Ukraine that serves as an important regional railway junction and administrative center within Kirovohrad Oblast.
  • 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: Zánka
Triple: [Balatonfüred District, containsSettlement, Zánka]
Generated description
Zánka is a small Hungarian village on the northern shore of Lake Balaton, known for its youth camp and scenic surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zánka
Target entity description: Zánka is a small Hungarian village on the northern shore of Lake Balaton, known for its youth camp and scenic surroundings.
  • A. Noznisky
    Noznisky is a relatively uncommon family surname associated with individuals such as Shirley Marlin Noznisky.
  • B. Koudelka
    Koudelka is a Czech surname most prominently associated with Josef Koudelka, the renowned photographer known for his powerful black-and-white images documenting Roma communities and political upheaval.
  • C. Kája
    Kája is a Czech diminutive form of the given name Karel.
  • D. Zedka
    Zedka is a fellow patient in Paulo Coelho’s novel "Veronika Decides to Die," known for her struggle with depression and her role in challenging Veronika’s understanding of madness and freedom.
  • E. Znamianka
    Znamianka is a city in central Ukraine that serves as an important regional railway junction and administrative center within Kirovohrad Oblast.
  • 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_69e0b4cd25088190b48ca9700cd24efc completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2f3473c81908c43a2ec242b1acd completed April 21, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a090074036081908b02a3553181c77c completed May 16, 2026, 11:40 p.m.
NEDg Description generation batch_6a090390e6a0819092dbae50a5845961 completed May 16, 2026, 11:53 p.m.
NED2 Entity disambiguation (via description) batch_6a090402f0708190910174b850dc779a completed May 16, 2026, 11:55 p.m.
Created at: April 16, 2026, 12:41 p.m.