Triple

T8357580
Position Surface form Disambiguated ID Type / Status
Subject Prince of Darkness E196717 entity
Predicate refersTo P37 FINISHED
Object Devil E38619 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: Devil | Statement: [Prince of Darkness, refersTo, Devil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Devil
Context triple: [Prince of Darkness, refersTo, Devil]
  • A. Šatan
    Šatan is a Slovak surname most famously borne by Miroslav Šatan, a prominent former professional ice hockey player and national team star.
  • B. the Devil chosen
    The Devil is a supernatural embodiment of evil and temptation, commonly depicted in religious and literary traditions as a powerful adversary who bargains for human souls.
  • C. Deabolis
    Deabolis was a medieval Balkan town of strategic importance in the Byzantine–Norman conflicts, known as the site where the Treaty of Devol was concluded.
  • D. Shatana
    Shatana is a character from the Nart sagas, the traditional epic cycle of the North Caucasus peoples.
  • E. El Diablo
    El Diablo is the famous nickname of Bolivian football legend Marco Etcheverry, a creative attacking midfielder renowned for his playmaking skills.
  • 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_69ca82f08b348190bfb7881944bbff6f completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb804b57f88190907a4e4e389caf5f completed March 31, 2026, 8:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce029ea6b48190aca98c579a4fbe94 completed April 2, 2026, 5:46 a.m.
Created at: March 30, 2026, 5:59 p.m.