Triple

T13518192
Position Surface form Disambiguated ID Type / Status
Subject Michael L. Printz Honor E322821 entity
Predicate appliesToForm P1129 FINISHED
Object fiction 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: fiction | Statement: [Michael L. Printz Honor, appliesToForm, fiction]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: appliesToForm
Context triple: [Michael L. Printz Honor, appliesToForm, fiction]
  • A. appliesTo chosen
    Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
  • B. appliesFrom
    Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
  • C. supportsForm
    Indicates that one entity provides compatibility or backing for a particular form, format, or type associated with another entity.
  • D. usesForm
    Indicates that one entity employs, applies, or operates through a particular form, format, or structured representation of something.
  • E. associatedWithForm
    Indicates a relationship in which something is linked or connected to a particular form, document, or structured representation.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa27f048190bed33a98e28c8d09 completed April 12, 2026, 2:43 p.m.
PD Predicate disambiguation batch_69dbae0b63748190b5e207f84b2532ea completed April 12, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:44 p.m.