Triple

T13626173
Position Surface form Disambiguated ID Type / Status
Subject Karaite synagogue in Ramla E325588 entity
Predicate doesNotFollow P2558 FINISHED
Object Oral Torah as binding law 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: Oral Torah as binding law | Statement: [Karaite synagogue in Ramla, doesNotFollow, Oral Torah as binding law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: doesNotFollow
Context triple: [Karaite synagogue in Ramla, doesNotFollow, Oral Torah as binding law]
  • A. doesNot
    Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
  • B. doesNotUse chosen
    Indicates that one entity intentionally refrains from employing, utilizing, or relying on another entity, method, or resource.
  • C. doesNotConsider
    Indicates that one entity fails or chooses not to take another entity or factor into account when forming judgments, decisions, or actions.
  • D. doesNotNecessarily
    Indicates that the specified condition, relationship, or outcome is not guaranteed to hold, even if other related conditions are true.
  • E. doesNotStandFor
    Indicates that one entity does not represent, symbolize, or act on behalf of another entity in any capacity.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc60635d08190899806fe8936f02a completed April 12, 2026, 4:19 p.m.
PD Predicate disambiguation batch_69dbbe85e1c4819095194f4b7f9f6118 completed April 12, 2026, 3:47 p.m.
Created at: April 9, 2026, 9:51 p.m.