Triple

T277570
Position Surface form Disambiguated ID Type / Status
Subject St Mary Magdalene Church, Woodstock E5281 entity
Predicate dedicatedTo P500 FINISHED
Object Mary Magdalene E19963 NE 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: Mary Magdalene | Statement: [St Mary Magdalene Church, Woodstock, dedicatedTo, Mary Magdalene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Magdalene
Context triple: [St Mary Magdalene Church, Woodstock, dedicatedTo, Mary Magdalene]
  • A. Mary Magdalene chosen
    Mary Magdalene is a prominent New Testament figure known as a devoted follower of Jesus who witnessed his crucifixion and was the first to see the resurrected Christ.
  • B. Pauline
    Pauline is a feminine given name used in various languages, often considered the female form of Paul.
  • C. Virgin Mary
    The Virgin Mary is revered in Christianity as the mother of Jesus Christ and a central figure of faith, purity, and devotion.
  • D. Sister Margaret
    Sister Margaret is a central nun protagonist in the film "Come to the Stable," known for her faith-driven determination and gentle leadership.
  • E. Saint Barbara
    Saint Barbara is a Christian martyr venerated as the patron saint of artillerymen, military engineers, and others who work with explosives and dangerous occupations.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25ded68c88190b1fc595ce329aeb9 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a394a13b688190951b070facd01d8c completed March 1, 2026, 1:21 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.