Triple

T2284167
Position Surface form Disambiguated ID Type / Status
Subject Hollywood North E51347 entity
Predicate hasNotableCityFeature P1495 FINISHED
Object urban landscapes used as filming locations LITERAL 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: urban landscapes used as filming locations | Statement: [Hollywood North, hasNotableCityFeature, urban landscapes used as filming locations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNotableCityFeature
Context triple: [Hollywood North, hasNotableCityFeature, urban landscapes used as filming locations]
  • A. hasNotableTown
    Indicates that an entity includes or is associated with a town that is considered notable or significant in some way.
  • B. hasUrbanFeature chosen
    Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
  • C. hasFamousCity
    Indicates that an entity possesses or is associated with a city that is widely recognized or renowned.
  • D. notableInCity
    Indicates that an entity is particularly prominent, recognized, or significant within a specific city.
  • E. hasMajorCity
    Indicates that a location possesses at least one city of significant size, importance, or influence within its region or country.
  • F. None of above.

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_69a88b08e4308190bdac9aebcca1c91a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc2445f388190af643878145f8249 completed March 7, 2026, 6:14 a.m.
PD Predicate disambiguation batch_69abbdbb9e4c819085fc588626ec7c09 completed March 7, 2026, 5:55 a.m.
Created at: March 4, 2026, 7:48 p.m.