Triple

T14059731
Position Surface form Disambiguated ID Type / Status
Subject Heves County E338311 entity
Predicate contains P35 FINISHED
Object Heves
Heves is a town in northern Hungary that serves as a local administrative and cultural center within Heves County.
 E1078682 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: Heves | Statement: [Heves County, contains, Heves]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Heves
Context triple: [Heves County, contains, Heves]
  • A. Tihany
    Tihany is a historic village on the northern shore of Lake Balaton in Hungary, renowned for its Benedictine abbey, scenic peninsula, and traditional architecture.
  • B. Bodrogköz
    Bodrogköz is a low-lying, marshy region in northeastern Hungary known for its riverine landscapes, wetlands, and traditional rural settlements.
  • C. Trencsén
    Trencsén is a historic town in present-day Slovakia, known for its medieval castle and its role as an important regional center in the former Upper Hungary.
  • D. Dunaharaszti
    Dunaharaszti is a town in central Hungary that functions largely as a suburban residential and industrial area near Budapest.
  • E. Bácska
    Bácska is a historical region in the Pannonian Plain, today divided between northern Serbia and southern Hungary, known for its multicultural population and agricultural importance.
  • 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: Heves
Triple: [Heves County, contains, Heves]
Generated description
Heves is a town in northern Hungary that serves as a local administrative and cultural center within Heves County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Heves
Target entity description: Heves is a town in northern Hungary that serves as a local administrative and cultural center within Heves County.
  • A. Tihany
    Tihany is a historic village on the northern shore of Lake Balaton in Hungary, renowned for its Benedictine abbey, scenic peninsula, and traditional architecture.
  • B. Bodrogköz
    Bodrogköz is a low-lying, marshy region in northeastern Hungary known for its riverine landscapes, wetlands, and traditional rural settlements.
  • C. Trencsén
    Trencsén is a historic town in present-day Slovakia, known for its medieval castle and its role as an important regional center in the former Upper Hungary.
  • D. Dunaharaszti
    Dunaharaszti is a town in central Hungary that functions largely as a suburban residential and industrial area near Budapest.
  • E. Bácska
    Bácska is a historical region in the Pannonian Plain, today divided between northern Serbia and southern Hungary, known for its multicultural population and agricultural importance.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5686f51c81908c33143ecbaae83d completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb662c37c8190a629278a97060080 completed May 7, 2026, 3:57 p.m.
NEDg Description generation batch_69fcc99fca8c8190bbcafba5bacfdfda completed May 7, 2026, 5:19 p.m.
NED2 Entity disambiguation (via description) batch_69fcca3a375c819092b3f67612d2ec0c completed May 7, 2026, 5:22 p.m.
Created at: April 9, 2026, 10:21 p.m.