Triple

T3580285
Position Surface form Disambiguated ID Type / Status
Subject Mary E75782 entity
Predicate hasVariant P455 FINISHED
Object Mária
Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
E370388 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: Mária | Statement: [Mary, hasVariant, Mária]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mária
Context triple: [Mary, hasVariant, Mária]
  • A. Terézia Mora
    Terézia Mora is a Hungarian-born German writer and translator acclaimed for her innovative prose and contributions to contemporary German-language literature.
  • B. Terézia
    Terézia is the given name of the Hungarian-born German writer and translator Terézia Mora, known for her award-winning novels and screenplays.
  • C. Katalin
    Katalin is a Hungarian given name most prominently associated with biochemist Katalin Karikó, a pioneer of mRNA technology used in COVID-19 vaccines.
  • D. Zora Vesecká
    Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
  • E. Júlia
    Júlia is the given name of Julia Warhola, the mother of American pop artist Andy Warhol.
  • 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: Mária
Triple: [Mary, hasVariant, Mária]
Generated description
Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mária
Target entity description: Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
  • A. Terézia Mora
    Terézia Mora is a Hungarian-born German writer and translator acclaimed for her innovative prose and contributions to contemporary German-language literature.
  • B. Terézia
    Terézia is the given name of the Hungarian-born German writer and translator Terézia Mora, known for her award-winning novels and screenplays.
  • C. Katalin
    Katalin is a Hungarian given name most prominently associated with biochemist Katalin Karikó, a pioneer of mRNA technology used in COVID-19 vaccines.
  • D. Zora Vesecká
    Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
  • E. Júlia
    Júlia is the given name of Julia Warhola, the mother of American pop artist Andy Warhol.
  • 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_69ad85d5e3008190bdfe0bacdd1f5a1b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0ffecdc8190bf01c8ba90e3733e completed March 8, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bbc95fa881909846a6d53ba6a24e completed March 13, 2026, 7:24 a.m.
NEDg Description generation batch_69b3bcae84a48190b085f253773cd14f completed March 13, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_69b3f90df47c81908855021f68ca7ec8 completed March 13, 2026, 11:46 a.m.
Created at: March 8, 2026, 3:21 p.m.