Triple

T7288309
Position Surface form Disambiguated ID Type / Status
Subject In Too Deep E163929 entity
Predicate hasCharacter P2308 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: [In Too Deep, hasCharacter, Myra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Myra
Context triple: [In Too Deep, hasCharacter, 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. Sarina
    Sarina is a Dutch football manager and former player best known for coaching top international women’s national teams, including the Netherlands and England.
  • 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_69c6886093b88190a254b1ce6db8bae7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb6a73fc8190ae5ce81fd3e46d87 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db4671e08190874d5e099e883509 completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 2:59 p.m.