Triple

T1913056
Position Surface form Disambiguated ID Type / Status
Subject Miskolc E38152 entity
Predicate hasNearbyAttraction P2064 FINISHED
Object Lillafüred
Lillafüred is a scenic resort area in northern Hungary known for its historic palace hotel, hanging gardens, and proximity to natural attractions like caves and waterfalls.
 E215798 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: Lillafüred | Statement: [Miskolc, hasNearbyAttraction, Lillafüred]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lillafüred
Context triple: [Miskolc, hasNearbyAttraction, Lillafüred]
  • A. Llaillay
    Llaillay is a Chilean town and commune in the Valparaíso Region, known for its agricultural activity and location in the Aconcagua Valley.
  • B. Leijonat
    Leijonat is the widely used Finnish nickname for Finland’s men’s national ice hockey team, literally meaning “The Lions.”
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Fonyód
    Fonyód is a Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, marinas, and panoramic views of the lake and surrounding hills.
  • E. Märsta
    Märsta is a town in Stockholm County, Sweden, known as a residential and transport hub near Stockholm Arlanda Airport.
  • 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: Lillafüred
Triple: [Miskolc, hasNearbyAttraction, Lillafüred]
Generated description
Lillafüred is a scenic resort area in northern Hungary known for its historic palace hotel, hanging gardens, and proximity to natural attractions like caves and waterfalls.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lillafüred
Target entity description: Lillafüred is a scenic resort area in northern Hungary known for its historic palace hotel, hanging gardens, and proximity to natural attractions like caves and waterfalls.
  • A. Llaillay
    Llaillay is a Chilean town and commune in the Valparaíso Region, known for its agricultural activity and location in the Aconcagua Valley.
  • B. Leijonat
    Leijonat is the widely used Finnish nickname for Finland’s men’s national ice hockey team, literally meaning “The Lions.”
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Fonyód
    Fonyód is a Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, marinas, and panoramic views of the lake and surrounding hills.
  • E. Märsta
    Märsta is a town in Stockholm County, Sweden, known as a residential and transport hub near Stockholm Arlanda Airport.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1e26b948190aa194c30755ac5df completed March 7, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3d5972881908856b75b324a1ad2 completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf44290748190b882559de536af09 completed March 8, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69adf4d0ac58819096659706ef0785d0 completed March 8, 2026, 10:14 p.m.
Created at: March 4, 2026, 7:35 p.m.