Triple

T3580274
Position Surface form Disambiguated ID Type / Status
Subject Mary E75782 entity
Predicate hasVariant P455 FINISHED
Object Marya
Marya is a feminine given name, often considered a variant of Mary and used in various cultures and languages.
E370383 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: Marya | Statement: [Mary, hasVariant, Marya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marya
Context triple: [Mary, hasVariant, Marya]
  • A. Romeyka
    Romeyka is an endangered Greek dialect spoken mainly in northeastern Turkey, notable for preserving many archaic features of Ancient Greek.
  • B. Sharya
    Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
  • C. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • D. Marida
    Marida was the mother of the Abbasid caliph al-Mu'tasim, placing her within the influential familial circle of the Abbasid dynasty.
  • E. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • 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: Marya
Triple: [Mary, hasVariant, Marya]
Generated description
Marya is a feminine given name, often considered a variant of Mary and used in various cultures and languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marya
Target entity description: Marya is a feminine given name, often considered a variant of Mary and used in various cultures and languages.
  • A. Romeyka
    Romeyka is an endangered Greek dialect spoken mainly in northeastern Turkey, notable for preserving many archaic features of Ancient Greek.
  • B. Sharya
    Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
  • C. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • D. Marida
    Marida was the mother of the Abbasid caliph al-Mu'tasim, placing her within the influential familial circle of the Abbasid dynasty.
  • E. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • 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.