Triple

T22797148
Position Surface form Disambiguated ID Type / Status
Subject Molnar E564279 entity
Predicate hasVariant P455 FINISHED
Object Molnárné
Molnárné is a Hungarian feminine surname form indicating “Mrs. Molnár,” traditionally used to denote the wife of someone with the surname Molnár.
 E1559149 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: Molnárné | Statement: [Molnar, hasVariant, Molnárné]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Molnárné
Context triple: [Molnar, hasVariant, Molnárné]
  • A. Molnari
    Molnari is a variant form of the surname Molnar, which is of Hungarian origin and traditionally associated with the occupation of miller.
  • B. Mihulová
    Mihulová is a Czech surname most notably borne by the award-winning Czech actress Alena Mihulová.
  • C. Mlyny
    Mlyny is a village in present-day Poland historically associated with Ukrainian cultural figures, including as the place where composer Mykhailo Verbytsky died.
  • D. Slaná
    Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
  • E. Maroško
    Maroško is a literary work by Slovak writer Martin Rázus, known as a classic of early 20th-century Slovak literature.
  • 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: Molnárné
Triple: [Molnar, hasVariant, Molnárné]
Generated description
Molnárné is a Hungarian feminine surname form indicating “Mrs. Molnár,” traditionally used to denote the wife of someone with the surname Molnár.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Molnárné
Target entity description: Molnárné is a Hungarian feminine surname form indicating “Mrs. Molnár,” traditionally used to denote the wife of someone with the surname Molnár.
  • A. Molnari
    Molnari is a variant form of the surname Molnar, which is of Hungarian origin and traditionally associated with the occupation of miller.
  • B. Mihulová
    Mihulová is a Czech surname most notably borne by the award-winning Czech actress Alena Mihulová.
  • C. Mlyny
    Mlyny is a village in present-day Poland historically associated with Ukrainian cultural figures, including as the place where composer Mykhailo Verbytsky died.
  • D. Slaná
    Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
  • E. Maroško
    Maroško is a literary work by Slovak writer Martin Rázus, known as a classic of early 20th-century Slovak literature.
  • 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_69e2458185f88190b0045227ee420411 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17cd9b3c0819096050f43a829ec0d completed April 29, 2026, 3:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bae7cb01881908513e1b35a766fce completed May 19, 2026, 12:27 a.m.
NEDg Description generation batch_6a0bb0011dfc8190abb4b0dc9dd8c018 completed May 19, 2026, 12:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0bb0944ba48190974df20fc1f1b8c8 completed May 19, 2026, 12:36 a.m.
Created at: April 17, 2026, 3:30 p.m.