Triple

T15941460
Position Surface form Disambiguated ID Type / Status
Subject Jere Burns E386573 entity
Predicate notableWork P4 FINISHED
Object Dear John E570306 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: Dear John | Statement: [Jere Burns, notableWork, Dear John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dear John
Context triple: [Jere Burns, notableWork, Dear John]
  • A. Dear John chosen
    Dear John is an American sitcom that aired from 1988 to 1992, starring Judd Hirsch as a recently divorced man navigating single life and friendships in a New York City support group.
  • B. Dear John
    "Dear John" is a six-minute country-pop ballad by Taylor Swift widely noted for its confessional lyrics about a toxic relationship and emotional manipulation.
  • C. Dear John
    Dear John is a romantic drama film based on Nicholas Sparks' novel, following the relationship between a soldier and a young woman whose love is tested by distance and time.
  • D. Dear John Letter
    "Dear John Letter" is a song from Whitney Houston's 2002 album "Just Whitney," reflecting themes of heartbreak and the end of a relationship.
  • E. Dear Michael
    Dear Michael is a work by Italian author Natalia Ginzburg, reflecting her characteristic blend of intimate psychological insight and understated, autobiographical storytelling.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156ce0230819089a20114a755a75a completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5bbc07c819098fd768e2e6b5b3e completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:53 a.m.