Triple

T8617364
Position Surface form Disambiguated ID Type / Status
Subject Myra Gardner E204073 entity
Predicate givenName P17 FINISHED
Object Myra E205620 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: Myra | Statement: [Myra Gardner, givenName, Myra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Myra
Context triple: [Myra Gardner, givenName, Myra]
  • A. Myra chosen
    Myra is a feminine given name used in various cultures, often associated with individuals of Jewish and English-speaking backgrounds.
  • B. Myra
    Myra was an ancient Greek city in Lycia, in what is now southwestern Turkey, historically notable as a major early Christian center and the bishopric of Saint Nicholas.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • E. Moura
    Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
  • 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_69ca832ceab8819096e4a9f546695079 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc4711c7748190af26ff5a78ef66a2 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbc1d8a08190bbcf7c4cef0fe04d completed April 2, 2026, 6:56 p.m.
Created at: March 30, 2026, 6:26 p.m.