Triple

T10102210
Position Surface form Disambiguated ID Type / Status
Subject Hunyadi family E216228 entity
Predicate titleHeld P7034 FINISHED
Object Count of Beszterce
Count of Beszterce was a noble title in the Kingdom of Hungary historically associated with the influential Hunyadi family.
 E840040 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: Count of Beszterce | Statement: [Hunyadi family, titleHeld, Count of Beszterce]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Count of Beszterce
Context triple: [Hunyadi family, titleHeld, Count of Beszterce]
  • A. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • B. Nagyatád
    Nagyatád is a small town in southwestern Hungary known for its thermal baths and surrounding rural landscapes.
  • C. Mátészalka
    Mátészalka is a town in northeastern Hungary known as a local administrative and economic center within the Northern Great Plain region.
  • 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. Ercsi
    Ercsi is a small town in central Hungary situated along the Danube River in Fejér County.
  • 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: Count of Beszterce
Triple: [Hunyadi family, titleHeld, Count of Beszterce]
Generated description
Count of Beszterce was a noble title in the Kingdom of Hungary historically associated with the influential Hunyadi family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Count of Beszterce
Target entity description: Count of Beszterce was a noble title in the Kingdom of Hungary historically associated with the influential Hunyadi family.
  • A. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • B. Nagyatád
    Nagyatád is a small town in southwestern Hungary known for its thermal baths and surrounding rural landscapes.
  • C. Mátészalka
    Mátészalka is a town in northeastern Hungary known as a local administrative and economic center within the Northern Great Plain region.
  • 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. Ercsi
    Ercsi is a small town in central Hungary situated along the Danube River in Fejér County.
  • 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_69ca83d039f08190b9d10363221c69fb completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd099c21c819097aac4f0f168a2da completed April 2, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b6d3efec8190b1432ca614aeb334 completed April 5, 2026, 7:24 p.m.
NEDg Description generation batch_69d2b7af6c188190b26cfd9da9e29d3d 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, 9:02 p.m.