Triple

T2685716
Position Surface form Disambiguated ID Type / Status
Subject Podlasie E57478 entity
Predicate traditionalReligionMix P24121 FINISHED
Object Catholic–Orthodox borderland 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: Catholic–Orthodox borderland | Statement: [Podlasie, traditionalReligionMix, Catholic–Orthodox borderland]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: traditionalReligionMix
Context triple: [Podlasie, traditionalReligionMix, Catholic–Orthodox borderland]
  • A. traditionalReligionName
    Indicates that an entity has a name specifically associated with a traditional or indigenous religion.
  • B. religiousTraditions chosen
    Indicates a relationship where certain religious customs, practices, or belief systems are associated with or observed by an entity.
  • C. laterReligion
    Indicates that one religion or religious affiliation chronologically follows or replaces another for the same entity.
  • D. practicesReligion
    Indicates that an entity actively follows, observes, or participates in the beliefs, rituals, and customs of a particular religion.
  • E. religiousTarget
    Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9ef2fe0819082bbe746ca682a7e completed March 7, 2026, 7:55 a.m.
PD Predicate disambiguation batch_69abd81c9b4c81908e5e0da6ac5f828b completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:54 p.m.