Triple

T207927
Position Surface form Disambiguated ID Type / Status
Subject Miryam E4648 entity
Predicate hasVariant P455 FINISHED
Object Maria E27948 NE FINISHED

How this triple was built (2 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: Maria | Statement: [Miryam, hasVariant, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria
Context triple: [Miryam, hasVariant, Maria]
  • A. Mary
    Mary, Princess Royal and Countess of Harewood, was a daughter of King George V and Queen Mary of the United Kingdom and a prominent British royal figure in the early to mid-20th century.
  • B. Mary
    Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
  • C. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • D. Marie chosen
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • E. Zoila Augusta Emperatriz Chávarri del Castillo
    Zoila Augusta Emperatriz Chávarri del Castillo, better known as Yma Sumac, was a renowned Peruvian soprano celebrated for her extraordinary vocal range and exoticized recordings in the 1950s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a25737567c81908f9c505300239181 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c071fac81908f706d1384281182 completed Feb. 28, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69a37952cbbc8190afd920510408fd31 completed Feb. 28, 2026, 11:25 p.m.
Created at: Feb. 28, 2026, 2:51 a.m.