Triple

T7392939
Position Surface form Disambiguated ID Type / Status
Subject Churche E170545 entity
Predicate orthographicVariantType P33995 FINISHED
Object alternative spelling 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: alternative spelling | Statement: [Churche, orthographicVariantType, alternative spelling]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: orthographicVariantType
Context triple: [Churche, orthographicVariantType, alternative spelling]
  • A. orthographicVariant chosen
    Indicates that two written forms are different spellings or orthographic representations of the same linguistic item.
  • B. orthographicProperty
    Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
  • C. hasOrthographicConvention
    Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
  • D. hasOrthographicReform
    Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
  • E. 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).
  • 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_69c68a5e2c9081909e713ce866e0060a completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f224790c819099ceb7c7ac8d00f6 completed March 27, 2026, 9:09 p.m.
PD Predicate disambiguation batch_69c6f0309cc88190b55d278969400294 completed March 27, 2026, 9:01 p.m.
Created at: March 27, 2026, 3:09 p.m.