Triple

T1129649
Position Surface form Disambiguated ID Type / Status
Subject re-BECK-a E22998 entity
Predicate usesOrthographicHighlighting P12752 FINISHED
Object capitalization of BECK 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: capitalization of BECK | Statement: [re-BECK-a, usesOrthographicHighlighting, capitalization of BECK]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesOrthographicHighlighting
Context triple: [re-BECK-a, usesOrthographicHighlighting, capitalization of BECK]
  • A. hasOrthographicPreference
    Indicates that one entity prefers or selects a particular written or spelling form of another entity.
  • B. orthographicProperty chosen
    Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
  • C. hasOrthographicReform
    Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
  • D. orthographicRole
    Indicates the functional role that a written form or spelling plays within an orthographic system (e.g., as a letter, diacritic, punctuation mark, or other script element).
  • E. hasStandardOrthographySince
    Indicates that a language or writing system has used a particular standardized orthography starting from a specified point in time.
  • 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_69a493ec75988190b63a11bafaec29b4 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc4bc21881909dcfe628f59f3e8c completed March 1, 2026, 10:23 p.m.
PD Predicate disambiguation batch_69a4bb48de2081909a0dce005b1c9df1 completed March 1, 2026, 10:18 p.m.
Created at: March 1, 2026, 7:44 p.m.