Triple

T14748584
Position Surface form Disambiguated ID Type / Status
Subject Moon Witch, Spider King E346538 entity
Predicate mainCharacter P1183 FINISHED
Object Sogolon E1118000 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: Sogolon | Statement: [Moon Witch, Spider King, mainCharacter, Sogolon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sogolon
Context triple: [Moon Witch, Spider King, mainCharacter, Sogolon]
  • A. Sogolon chosen
    Sogolon is the central character of Marlon James's fantasy novel "Moon Witch, Spider King," depicted as a powerful and long-lived witch navigating a brutal, mythic African-inspired world.
  • B. Tashmetu
    Tashmetu is a Mesopotamian goddess associated with mercy and the granting of prayers, venerated alongside the god Nabu.
  • C. Princess Ahmanet
    Princess Ahmanet is the vengeful ancient Egyptian royal and primary antagonist in the 2017 film "The Mummy."
  • D. Zeleia
    Zeleia was an ancient city in the region of Mysia in northwestern Asia Minor, known from classical Greek and Roman historical and geographical sources.
  • E. Nanisca
    Nanisca is a fierce and strategic general of the all-female Agojie warriors in the historical epic film "The Woman King."
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d2e1748190b16ede681fe52872 completed April 14, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0ce843a481908f376172d4a8b70a completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:30 a.m.