Triple

T35258865
Position Surface form Disambiguated ID Type / Status
Subject Orlando (given name) E1018313 entity
Predicate hasLiteraryBearer P197680 FINISHED
Object Orlando (Shakespeare character) NE NERFINISHED

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: Orlando (Shakespeare character) | Statement: [Orlando (given name), hasLiteraryBearer, Orlando (Shakespeare character)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLiteraryBearer
Context triple: [Orlando (given name), hasLiteraryBearer, Orlando (Shakespeare character)]
  • A. hasLiteraryConnection
    Indicates a relationship in which one entity is connected to another through a literary link, such as authorship, reference, influence, adaptation, or shared appearance in written works.
  • B. hasLiterarySignificance
    Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
  • C. literaryAuthor
    Indicates that one entity is the author or writer of a literary work represented by the other entity.
  • D. hasLiteraryForm
    Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
  • E. hasLiteraryStandard
    Indicates that one entity defines, specifies, or embodies the accepted literary norm or standard used by another entity.
  • F. None of above. chosen

Provenance (4 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_69f76de4be5c8190a51705c07612cac8 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fea1f5d8c481908dc3351dc9ecef7f completed May 9, 2026, 2:54 a.m.
PD Predicate disambiguation batch_69fea06b6fe0819095bf4c1bc9809927 completed May 9, 2026, 2:48 a.m.
PDg Predicate description generation batch_69fea1f4daa88190bd3cc1ace684e77f completed May 9, 2026, 2:54 a.m.
Created at: May 3, 2026, 4:02 p.m.