Triple

T5622372
Position Surface form Disambiguated ID Type / Status
Subject Viva bus rapid transit E147637 entity
Predicate hasLine P35 FINISHED
Object Viva Blue E196947 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: Viva Blue | Statement: [Viva bus rapid transit, hasLine, Viva Blue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viva Blue
Context triple: [Viva bus rapid transit, hasLine, Viva Blue]
  • A. Viva chosen
    Viva is a bus rapid transit service in York Region, Ontario, Canada, providing frequent, limited-stop public transportation along major corridors.
  • B. Viva
    Viva is a German music television channel that gained popularity in the 1990s and 2000s for its music videos, pop culture programming, and youth-oriented shows.
  • C. Red, Hot and Blue
    Red, Hot and Blue is a 1936 Broadway musical comedy with music and lyrics by Cole Porter, known for its witty songs and star-studded original cast.
  • D. Into the Blue
    Into the Blue is a 2005 action-thriller film about a group of divers who discover a sunken plane full of drugs, starring Paul Walker and Jessica Alba.
  • E. Under a Blanket of Blue
    "Under a Blanket of Blue" is a jazz standard best known for its smooth, romantic rendition by Ella Fitzgerald and Louis Armstrong.
  • 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_69c00906f2a88190a992c66b13d606d4 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c022133eec819086acb04864dde5ee completed March 22, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d5da9cc819097281dd6aa405e62 completed March 22, 2026, 8:13 p.m.
Created at: March 22, 2026, 3:40 p.m.