Triple

T5246172
Position Surface form Disambiguated ID Type / Status
Subject I Love You to Death E118463 entity
Predicate mainCharacter P1183 FINISHED
Object Harlan E193721 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: Harlan | Statement: [I Love You to Death, mainCharacter, Harlan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harlan
Context triple: [I Love You to Death, mainCharacter, Harlan]
  • A. Harlan chosen
    Harlan is a masculine given name of English origin, historically associated with figures such as U.S. Chief Justice Harlan F. Stone.
  • B. De Witt
    De Witt is a Dutch surname most famously associated with Johan de Witt, a prominent 17th-century statesman of the Dutch Republic.
  • C. Andrew Harlan
    Andrew Harlan is the time-manipulating Technician protagonist of Isaac Asimov’s science fiction novel "The End of Eternity."
  • D. Daggett
    Daggett is a small unincorporated desert community in San Bernardino County, California, historically known as a railroad and mining town along major transportation routes.
  • E. Shaughnessy
    Shaughnessy is an affluent residential neighbourhood in Vancouver, British Columbia, known for its large heritage homes and tree-lined streets.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b515edc8190a9db198d4eb1c4f6 completed March 20, 2026, 4:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef832ae8481908a90faf66c1db631 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:49 p.m.