Triple

T34891677
Position Surface form Disambiguated ID Type / Status
Subject Daisy E1006302 entity
Predicate featuredInCountry P626 FINISHED
Object American cinema 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: American cinema | Statement: [Daisy, featuredInCountry, American cinema]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuredInCountry
Context triple: [Daisy, featuredInCountry, American cinema]
  • A. listedInCountry
    Indicates that an entity is officially recorded, registered, or included within the context or jurisdiction of a specified country.
  • B. countryFeatured
    Indicates that a particular country is highlighted or given special prominence in a given context or presentation.
  • C. displayedInCountry
    Indicates that something is shown, exhibited, or made visible within the boundaries of a specified country.
  • D. featuredIn chosen
    Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
  • E. meetsInCountry
    Indicates that two or more entities have an in-person meeting that takes place within the specified 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_69f76dbfe5788190ad8b64f241f470c8 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_6a036fb4650c81908df9b9ec8ed8594b completed May 12, 2026, 6:21 p.m.
PD Predicate disambiguation batch_6a036f64dc648190a31cf944d3ea0f7d completed May 12, 2026, 6:20 p.m.
Created at: May 3, 2026, 4 p.m.