Triple

T19162186
Position Surface form Disambiguated ID Type / Status
Subject Ayn Sof E469082 entity
Predicate transliterationVariant P5923 FINISHED
Object En Sof NE NERFINISHED

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: En Sof | Statement: [Ayn Sof, transliterationVariant, En Sof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: En Sof
Context triple: [Ayn Sof, transliterationVariant, En Sof]
  • A. En Sof chosen
    En Sof is a Kabbalistic term for the infinite, unknowable aspect of God that precedes and transcends all creation.
  • B. La Vera
    La Vera is a picturesque comarca in northern Extremadura, Spain, known for its lush landscapes, traditional villages, and production of smoked paprika (pimentón).
  • C. Santiponce
    Santiponce is a municipality in the province of Seville, Spain, known for encompassing the archaeological site of the ancient Roman city of Italica.
  • D. Ontinyent
    Ontinyent is a historic town in eastern Spain known for its textile industry, traditional festivals, and scenic setting along the Clariano River.
  • E. Pozondón
    Pozondón is a small rural municipality in the province of Teruel, Aragon, Spain, known for its highland landscapes and traditional architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5eebe03ac8190bbe0b34ebf0d90c6 completed April 20, 2026, 9:15 a.m.
Created at: April 10, 2026, 12:06 p.m.