Triple

T8323130
Position Surface form Disambiguated ID Type / Status
Subject Glastonbury Tor E194881 entity
Predicate associatedWithDeity P1481 FINISHED
Object Archangel Michael E50376 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: Archangel Michael | Statement: [Glastonbury Tor, associatedWithDeity, Archangel Michael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Archangel Michael
Context triple: [Glastonbury Tor, associatedWithDeity, Archangel Michael]
  • A. Saint Michael chosen
    Saint Michael is an archangel in Christian, Jewish, and Islamic traditions, revered as a protector, leader of the heavenly hosts, and vanquisher of evil.
  • B. Seraphim
    Seraphim are the highest-ranking class of angels in Christian angelology, traditionally associated with fiery devotion and the worship of God.
  • C. Raphael (archangel)
    Raphael is an archangel in Judeo-Christian tradition, often associated with healing and guidance, notably appearing in the deuterocanonical Book of Tobit.
  • D. Angel
    Angel is a given name used across various cultures, often associated with spiritual or celestial connotations.
  • E. Angel
    "Angel" is a 1937 romantic comedy film directed by Ernst Lubitsch, known for its sophisticated wit and starring Marlene Dietrich, Herbert Marshall, and Melvyn Douglas.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f7cf49c8190b8440ff01926a66a completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce0278b9a88190a57a6b1b31c39ee8 completed April 2, 2026, 5:45 a.m.
Created at: March 30, 2026, 5:56 p.m.