Triple

T9437852
Position Surface form Disambiguated ID Type / Status
Subject Idabel Thompkins E227560 entity
Predicate hasCloseFriend P49697 FINISHED
Object Joel Knox E235774 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: Joel Knox | Statement: [Idabel Thompkins, hasCloseFriend, Joel Knox]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joel Knox
Context triple: [Idabel Thompkins, hasCloseFriend, Joel Knox]
  • A. Joel Knox chosen
    Joel Knox is the introspective young boy at the center of Truman Capote’s Southern Gothic novel "Other Voices, Other Rooms," whose journey to find his estranged father doubles as a haunting exploration of identity and sexuality.
  • B. Jason Boesel
    Jason Boesel is an American drummer and songwriter best known for his work with the band Rilo Kiley and collaborations with various indie rock artists.
  • C. Ryan Dusick
    Ryan Dusick is an American musician best known as the original drummer and a founding member of the pop rock band Maroon 5.
  • D. Kyle Rote
    Kyle Rote was a former New York Giants star running back and wide receiver who became a prominent American sportscaster and television commentator.
  • E. Trent Baalke
    Trent Baalke is an American football executive best known for his tenure as an NFL general manager, including leading front offices for multiple franchises.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7edff5e881909b72976e8909ba4b completed April 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d11053d8008190a29575149d2e027f completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:50 p.m.