Triple

T2763838
Position Surface form Disambiguated ID Type / Status
Subject Dexter Scott King E61286 entity
Predicate givenName P17 FINISHED
Object Dexter E61286 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 | Statement: [Dexter Scott King, givenName, Dexter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dexter
Context triple: [Dexter Scott King, givenName, Dexter]
  • A. Dexter chosen
    Dexter is the given name of Dexter Scott King, an American civil and animal rights activist and the son of Martin Luther King Jr.
  • B. Dexter
    Dexter is a critically acclaimed American crime drama television series that follows a Miami forensic blood-spatter analyst who leads a secret life as a vigilante serial killer.
  • C. Detective Riley
    Detective Riley is a supporting police investigator character in the 2016 psychological thriller film "The Girl on the Train," involved in unraveling the central mystery.
  • D. The Killing
    The Killing is a 1956 film noir crime thriller directed by Stanley Kubrick about a meticulously planned racetrack heist that begins to unravel.
  • E. CSI: Miami
    CSI: Miami is an American police procedural television series that follows a team of forensic investigators solving crimes in Miami using advanced scientific techniques.
  • 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_69ab4b7bab6c8190a5c2efef19a8ef34 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd541c2c8190a983a6f6a0b24ed9 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc04630b8819081cd8ddac1d42184 completed March 10, 2026, 6:55 a.m.
Created at: March 6, 2026, 9:57 p.m.