Triple

T17622632
Position Surface form Disambiguated ID Type / Status
Subject National Flag Memorial E429747 entity
Predicate mainSymbolism P107935 FINISHED
Object ship cutting through the sea 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: ship cutting through the sea | Statement: [National Flag Memorial, mainSymbolism, ship cutting through the sea]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mainSymbolism
Context triple: [National Flag Memorial, mainSymbolism, ship cutting through the sea]
  • A. symbolismIn chosen
    Indicates that one entity functions as a symbol or representation within the context, meaning, or interpretive framework of another entity.
  • B. symbolismFocus
    Indicates that the primary emphasis of a work, element, or representation is on its symbolic meaning rather than its literal or functional aspects.
  • C. shapeSymbolism
    Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
  • D. incorporatesSymbolismFrom
    Indicates that one entity includes or integrates symbolic elements, motifs, or meanings derived from another entity.
  • E. typicalMaterialSymbolism
    Indicates that a material is commonly or characteristically used to symbolize or represent something in a given cultural or contextual setting.
  • 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_69d889e37f308190a6aa0a69daff86c7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46db98c54819088dadec9f6bcc559 completed April 19, 2026, 5:52 a.m.
PD Predicate disambiguation batch_69e3cdd7da34819099bc9481c5a79bab completed April 18, 2026, 6:30 p.m.
Created at: April 10, 2026, 5:52 a.m.