Triple

T10809545
Position Surface form Disambiguated ID Type / Status
Subject Mrs. Baylock E255059 entity
Predicate allegiance P1201 FINISHED
Object Satan E801462 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: Satan | Statement: [Mrs. Baylock, allegiance, Satan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Satan
Context triple: [Mrs. Baylock, allegiance, Satan]
  • A. Satan
    Satan is a central demonic figure and primary antagonist in the manga and anime series Blue Exorcist, portrayed as the powerful king of demons and the source of the protagonist’s conflict.
  • B. Satan chosen
    Satan is a central figure in Abrahamic religions, typically depicted as the embodiment of evil and the adversary of God and humankind.
  • C. Satana
    Satana is a town in the Nashik district of Maharashtra, India, known for its agricultural markets and proximity to several religious and historical sites.
  • D. Šatan
    Šatan is a Slovak surname most famously borne by Miroslav Šatan, a prominent former professional ice hockey player and national team star.
  • E. Iblis
    Iblis is the primary satanic figure in Islamic tradition, known for refusing to bow to Adam and subsequently leading humans astray.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733b6efc48190bb64b5a8fac843c4 completed April 9, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb0ea2b6481909dfd94fe0c3c4499 completed April 14, 2026, 9:26 p.m.
Created at: April 8, 2026, 9:18 p.m.