Triple

T3327128
Position Surface form Disambiguated ID Type / Status
Subject Racha E69941 entity
Predicate majorTown P316 FINISHED
Object Oni E60054 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: Oni | Statement: [Racha, majorTown, Oni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oni
Context triple: [Racha, majorTown, Oni]
  • A. Oni chosen
    Oni is a small town in the Racha region of northwestern Georgia, known for its mountainous surroundings and traditional Georgian architecture.
  • B. Zabivaka
    Zabivaka is the wolf character that served as the official mascot for major international football tournaments hosted by Russia, including the 2018 FIFA World Cup.
  • C. Grimus
    Grimus is Salman Rushdie’s debut novel, a genre-blending work of science fiction and fantasy that explores themes of identity, immortality, and exile.
  • D. Blixem
    Blixem is an alternative name for Blitzen, one of Santa Claus’s traditional flying reindeer known from the Christmas poem “A Visit from St. Nicholas.”
  • E. Undun
    Undun is a concept album by hip hop band The Roots that narrates the rise and fall of a fictional young man through introspective, jazz-influenced production and storytelling.
  • 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_69ad85a1829881908942c14075644d0d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb16dc170819086a63e033e17d8b3 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a7ce34c81908df0c30a41fd925c completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:12 p.m.