Triple

T8554380
Position Surface form Disambiguated ID Type / Status
Subject Tricolor das Laranjeiras E202527 entity
Predicate hasMeaningLiteral P3918 FINISHED
Object Tricolor of Laranjeiras 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: Tricolor of Laranjeiras | Statement: [Tricolor das Laranjeiras, hasMeaningLiteral, Tricolor of Laranjeiras]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMeaningLiteral
Context triple: [Tricolor das Laranjeiras, hasMeaningLiteral, Tricolor of Laranjeiras]
  • A. hasLiteralMeaning chosen
    Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
  • B. hasMeaningViaJohn
    Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
  • C. logicalMeaning
    Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
  • D. literalMeaningApproximation
    Indicates that one entity expresses an approximate or rough literal meaning of another entity, rather than an exact or fully precise interpretation.
  • E. hasSense
    Indicates that an entity possesses or is associated with a particular sensory perception, meaning, or interpretation.
  • 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_69ca832610e08190b3b6c6cd2c250255 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe8894e7c8190bc0ae2ceec473ecb completed March 31, 2026, 3:30 p.m.
PD Predicate disambiguation batch_69cbd1160fcc8190aa380a73610af731 completed March 31, 2026, 1:50 p.m.
Created at: March 30, 2026, 6:19 p.m.