Triple

T6222415
Position Surface form Disambiguated ID Type / Status
Subject Dexter E139146 entity
Predicate mainCharacter P1183 FINISHED
Object Dexter Morgan E403905 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: Dexter Morgan | Statement: [Dexter, mainCharacter, Dexter Morgan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dexter Morgan
Context triple: [Dexter, mainCharacter, Dexter Morgan]
  • A. Dexter Morgan chosen
    Dexter Morgan is the fictional forensic blood-spatter analyst and vigilante serial killer who serves as the antihero protagonist of the television series "Dexter."
  • B. Norman Colin Dexter
    Norman Colin Dexter was an English crime writer best known for creating the Inspector Morse detective novels.
  • C. Harlan Dexter
    Harlan Dexter is a wealthy, morally corrupt former actor turned powerful businessman who serves as a central antagonist in the darkly comedic neo-noir film "Kiss Kiss Bang Bang."
  • D. Michael Ripps
    Michael Ripps is a film editor known for his work on the movie "Stakeout."
  • E. Dexter's Dad
    Dexter's Dad is a bumbling yet well-meaning father from the animated series "Dexter's Laboratory," known for his suburban dad antics, love of bowling, and frequent obliviousness to his son's secret lab.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062bddb688190add53172a7445d01 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20dcc5e788190a510cac6bbad4830 completed March 24, 2026, 4:06 a.m.
Created at: March 22, 2026, 4:22 p.m.