Triple

T37515109
Position Surface form Disambiguated ID Type / Status
Subject Templar E932613 entity
Predicate startingAreaTheme P187803 FINISHED
Object faith and righteousness 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: faith and righteousness | Statement: [Templar, startingAreaTheme, faith and righteousness]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: startingAreaTheme
Context triple: [Templar, startingAreaTheme, faith and righteousness]
  • A. previousAreaTheme
    Indicates that one area’s theme directly precedes another area’s theme in a sequence or progression.
  • B. startTheme
    Indicates the action of initiating or activating a particular theme or thematic mode.
  • C. parkSectionTheme
    Indicates that a particular section of a park is associated with a specific thematic concept or style.
  • D. previousThemeParkArea
    Indicates that one theme park area directly preceded another in time or sequence within the park’s development or layout.
  • E. zoneTheme chosen
    Indicates that a particular zone or area is associated with, or characterized by, a specific theme or thematic 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_69f76ec730988190b5aa4f9cb9afd518 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_6a01185c46f0819089b4a2ad3c3e2f33 completed May 10, 2026, 11:44 p.m.
PD Predicate disambiguation batch_6a0117e19e008190870663dd45084416 completed May 10, 2026, 11:42 p.m.
Created at: May 3, 2026, 4:17 p.m.