Triple

T3809154
Position Surface form Disambiguated ID Type / Status
Subject Mici Mária Harkányi E93087 entity
Predicate familyName P18 FINISHED
Object Harkányi
Harkányi is a Hungarian surname associated with individuals such as Mici Mária Harkányi.
 E390415 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: Harkányi | Statement: [Mici Mária Harkányi, familyName, Harkányi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harkányi
Context triple: [Mici Mária Harkányi, familyName, Harkányi]
  • A. Sarolt
    Sarolt was a prominent 10th-century Hungarian noblewoman and duchess, influential in the Christianization and early state formation of Hungary as the wife of Grand Prince Géza and mother of King Stephen I.
  • B. Hadár
    Hadár is the guiding motto of the Betar youth movement, emphasizing Jewish pride, dignity, and disciplined self-respect.
  • C. 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.
  • D. Mátraháza
    Mátraháza is a small mountain resort village in northern Hungary, known for its scenic location in the Mátra range and its hiking and wellness tourism.
  • E. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian 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: Harkányi
Triple: [Mici Mária Harkányi, familyName, Harkányi]
Generated description
Harkányi is a Hungarian surname associated with individuals such as Mici Mária Harkányi.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harkányi
Target entity description: Harkányi is a Hungarian surname associated with individuals such as Mici Mária Harkányi.
  • A. Sarolt
    Sarolt was a prominent 10th-century Hungarian noblewoman and duchess, influential in the Christianization and early state formation of Hungary as the wife of Grand Prince Géza and mother of King Stephen I.
  • B. Hadár
    Hadár is the guiding motto of the Betar youth movement, emphasizing Jewish pride, dignity, and disciplined self-respect.
  • C. 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.
  • D. Mátraháza
    Mátraháza is a small mountain resort village in northern Hungary, known for its scenic location in the Mátra range and its hiking and wellness tourism.
  • E. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80c7fc48190b5c2400918bba5c2 completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb33db9c81908b462ee80aaaad34 completed March 14, 2026, 6:07 a.m.
NEDg Description generation batch_69b4fc08d65081908953482b10fa5611 completed March 14, 2026, 6:11 a.m.
NED2 Entity disambiguation (via description) batch_69b4fc7d8cf081909c4447818b5363c5 completed March 14, 2026, 6:13 a.m.
Created at: March 9, 2026, 3:16 p.m.