Triple

T9703630
Position Surface form Disambiguated ID Type / Status
Subject Pest County E234839 entity
Predicate hasSettlement P1068 FINISHED
Object Pilisvörösvár
Pilisvörösvár is a town in central Hungary known for its German minority heritage and proximity to Budapest.
E887087 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: Pilisvörösvár | Statement: [Pest County, hasSettlement, Pilisvörösvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pilisvörösvár
Context triple: [Pest County, hasSettlement, Pilisvörösvár]
  • A. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • B. Pécsvárad
    Pécsvárad is a small historic town in southern Hungary known for its medieval abbey and scenic setting near the Mecsek Mountains.
  • C. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • D. Törökbálint
    Törökbálint is a town in Pest County, Hungary, located just southwest of Budapest and known as a suburban residential area with growing commercial and industrial zones.
  • E. Tiszaföldvár
    Tiszaföldvár is a small town in eastern Hungary known for its agricultural surroundings and location near the Tisza River.
  • 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: Pilisvörösvár
Triple: [Pest County, hasSettlement, Pilisvörösvár]
Generated description
Pilisvörösvár is a town in central Hungary known for its German minority heritage and proximity to Budapest.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pilisvörösvár
Target entity description: Pilisvörösvár is a town in central Hungary known for its German minority heritage and proximity to Budapest.
  • A. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • B. Pécsvárad
    Pécsvárad is a small historic town in southern Hungary known for its medieval abbey and scenic setting near the Mecsek Mountains.
  • C. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • D. Törökbálint
    Törökbálint is a town in Pest County, Hungary, located just southwest of Budapest and known as a suburban residential area with growing commercial and industrial zones.
  • E. Tiszaföldvár
    Tiszaföldvár is a small town in eastern Hungary known for its agricultural surroundings and location near the Tisza River.
  • 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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d73a0148190ad4178fd462cdd9c completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69de83df5bf881908d775354ace05e66 completed April 14, 2026, 6:13 p.m.
NEDg Description generation batch_69de883488b481909f151d8a7c246aa1 completed April 14, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_69de8e80fe80819088ac76bb5abc58f0 completed April 14, 2026, 6:59 p.m.
Created at: March 30, 2026, 8:18 p.m.