Triple

T8336686
Position Surface form Disambiguated ID Type / Status
Subject Ventura Boulevard E195804 entity
Predicate hasPart P35 FINISHED
Object Tarzana E317979 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: Tarzana | Statement: [Ventura Boulevard, hasPart, Tarzana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarzana
Context triple: [Ventura Boulevard, hasPart, Tarzana]
  • A. Tarzana chosen
    Tarzana is a residential neighborhood in the San Fernando Valley region of Los Angeles, California, named after the fictional character Tarzan and known for its suburban character and proximity to the Santa Monica Mountains.
  • B. Glendale
    Glendale is a residential neighbourhood within the city of Pickering in Ontario, Canada.
  • C. Glendale
    Glendale is a city in Arizona known for hosting major sporting and entertainment events, including NFL games and the Super Bowl.
  • D. Glendale
    Glendale is a city in Los Angeles County, California, known for its diverse communities, shopping districts like the Americana at Brand, and proximity to both urban Los Angeles and the Verdugo Mountains.
  • E. Glendale
    Glendale is a primarily residential neighborhood in the central-southern part of Queens, New York City, known for its quiet streets, local shops, and proximity to major cemeteries and parks.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd3fc80819097b326119107ad4d completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce6ccf66d48190a457e0ea869b278e completed April 2, 2026, 1:19 p.m.
Created at: March 30, 2026, 5:57 p.m.