Triple

T4175262
Position Surface form Disambiguated ID Type / Status
Subject Douai E86459 entity
Predicate twinnedWith P1072 FINISHED
Object Kiskunfélegyháza
Kiskunfélegyháza is a town in central Hungary known for its historical market-town character and location in the Great Hungarian Plain.
 E418702 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: Kiskunfélegyháza | Statement: [Douai, twinnedWith, Kiskunfélegyháza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kiskunfélegyháza
Context triple: [Douai, twinnedWith, Kiskunfélegyháza]
  • A. Bicske
    Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
  • B. 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.
  • C. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • D. Komló
    Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
  • E. Parádfürdő
    Parádfürdő is a spa village in northern Hungary known for its mineral springs and scenic location within the Mátra mountain region.
  • 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: Kiskunfélegyháza
Triple: [Douai, twinnedWith, Kiskunfélegyháza]
Generated description
Kiskunfélegyháza is a town in central Hungary known for its historical market-town character and location in the Great Hungarian Plain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kiskunfélegyháza
Target entity description: Kiskunfélegyháza is a town in central Hungary known for its historical market-town character and location in the Great Hungarian Plain.
  • A. Bicske
    Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
  • B. 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.
  • C. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • D. Komló
    Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
  • E. Parádfürdő
    Parádfürdő is a spa village in northern Hungary known for its mineral springs and scenic location within the Mátra mountain region.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02e9370481908eda048724261c2b completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f564c9c8190bfc321c8ec2dac14 completed March 14, 2026, 3:31 p.m.
NEDg Description generation batch_69b58330b1d48190a3af96d3c0e7aa1b completed March 14, 2026, 3:48 p.m.
NED2 Entity disambiguation (via description) batch_69b583ba1fd8819092b7fe73a17dc406 completed March 14, 2026, 3:50 p.m.
Created at: March 9, 2026, 3:45 p.m.