Triple

T10202010
Position Surface form Disambiguated ID Type / Status
Subject Doom (2005 film) E238904 entity
Predicate starring P1507 FINISHED
Object Deobia Oparei E285406 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: Deobia Oparei | Statement: [Doom (2005 film), starring, Deobia Oparei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deobia Oparei
Context triple: [Doom (2005 film), starring, Deobia Oparei]
  • A. DeObia Oparei chosen
    DeObia Oparei is a British actor and playwright known for his roles in film and television, including appearances in projects like Game of Thrones and various major studio movies.
  • B. Tafi Agome
    Tafi Agome is a village where the Tafi language is traditionally spoken, likely located in the Volta Region of Ghana.
  • C. Titi Owusu Addo
    Titi Owusu Addo is the daughter of Ghanaian rapper Sarkodie and is occasionally mentioned in media related to his personal life.
  • D. Bassey Otu
    Bassey Otu is a Nigerian politician serving as the governor of Cross River State.
  • E. Aggrey Awori
    Aggrey Awori was a Ugandan politician, former minister, and opposition figure known for his presidential bid and earlier career as a diplomat and academic.
  • 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_69ca84e1ea088190b38162e43d4cfa8f completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdee4239c08190b40f5cc19c3db3c7 completed April 2, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d317fcdf18819092d0f3f216edffdc completed April 6, 2026, 2:18 a.m.
Created at: March 30, 2026, 9:14 p.m.