Triple

T10092746
Position Surface form Disambiguated ID Type / Status
Subject Northern Hungary E215782 entity
Predicate containsTown P847 FINISHED
Object Gyöngyösoroszi
Gyöngyösoroszi is a small village in northern Hungary known for its historical mining activities and scenic setting near the Mátra Mountains.
 E339338 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: Gyöngyösoroszi | Statement: [Northern Hungary, containsTown, Gyöngyösoroszi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gyöngyösoroszi
Context triple: [Northern Hungary, containsTown, Gyöngyösoroszi]
  • A. Oroszlány
    Oroszlány is a town in northwestern Hungary known historically for its coal mining and industrial character.
  • B. Gyöngyös
    Gyöngyös is a historic town in northern Hungary known as a gateway to the Mátra mountain range and its surrounding wine-producing region.
  • C. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • D. Törökszentmiklós
    Törökszentmiklós is a town in central-eastern Hungary known for its agricultural surroundings and location within the Great Hungarian Plain.
  • E. Somlyó
    Somlyó is a historical locality in the Kingdom of Hungary, best known as the birthplace of Stephen Báthory, who became King of Poland and Grand Duke of Lithuania in the 16th century.
  • 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: Gyöngyösoroszi
Triple: [Northern Hungary, containsTown, Gyöngyösoroszi]
Generated description
Gyöngyösoroszi is a small village in northern Hungary known for its historical mining activities and scenic setting near the Mátra Mountains.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gyöngyösoroszi
Target entity description: Gyöngyösoroszi is a small village in northern Hungary known for its historical mining activities and scenic setting near the Mátra Mountains.
  • A. Oroszlány
    Oroszlány is a town in northwestern Hungary known historically for its coal mining and industrial character.
  • B. Gyöngyös chosen
    Gyöngyös is a historic town in northern Hungary known as a gateway to the Mátra mountain range and its surrounding wine-producing region.
  • C. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • D. Törökszentmiklós
    Törökszentmiklós is a town in central-eastern Hungary known for its agricultural surroundings and location within the Great Hungarian Plain.
  • E. Somlyó
    Somlyó is a historical locality in the Kingdom of Hungary, best known as the birthplace of Stephen Báthory, who became King of Poland and Grand Duke of Lithuania in the 16th century.
  • F. None of above.

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_69ca83a4947c8190823a7495dc5d96ed completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd05c3c0c8190927580717429a4e5 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b6aecc488190a9af098f687327ed completed April 5, 2026, 7:23 p.m.
NEDg Description generation batch_69d2b7bb88348190a39908b34b7419b2 completed April 5, 2026, 7:27 p.m.
NED2 Entity disambiguation (via description) batch_69d2b81e7b948190baa417186aac284b completed April 5, 2026, 7:29 p.m.
Created at: March 30, 2026, 9:01 p.m.