Triple

T20620045
Position Surface form Disambiguated ID Type / Status
Subject Nyota Uhura E506675 entity
Predicate givenName P17 FINISHED
Object Nyota NE NERFINISHED

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: Nyota | Statement: [Nyota Uhura, givenName, Nyota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyota
Context triple: [Nyota Uhura, givenName, Nyota]
  • A. Nyota chosen
    Nyota is the first name of Nyota Uhura, the pioneering Star Trek communications officer known as one of the earliest prominent Black female characters in American television science fiction.
  • B. Mira
    Mira is a coastal municipality in central Portugal known for its beaches, lagoons, and natural landscapes.
  • C. Mira
    Mira is a town in the Veneto region of northern Italy, situated along the Brenta Canal between Venice and Padua and known for its historic Venetian villas.
  • D. Mira
    Mira is a key character in the television series "Spartacus: Vengeance," known as a former slave and love interest of Spartacus who becomes an active member of the rebellion.
  • E. Mira
    Mira is a small town in northern Ecuador’s Carchi Province, known for its Andean setting and agricultural surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abe0e22c81909f6efe21518e33f0 completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:41 a.m.