Triple

T13829083
Position Surface form Disambiguated ID Type / Status
Subject Justin DeYarmond Edison Vernon E332335 entity
Predicate notableWork P4 FINISHED
Object 22, A Million E65356 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: 22, A Million | Statement: [Justin DeYarmond Edison Vernon, notableWork, 22, A Million]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 22, A Million
Context triple: [Justin DeYarmond Edison Vernon, notableWork, 22, A Million]
  • A. 22, A Million chosen
    22, A Million is an experimental, genre-blending album by Bon Iver known for its fragmented song structures, heavy electronic manipulation, and introspective, cryptic lyricism.
  • B. One in a Million
    "One in a Million" is a country song by American singer Johnny Lee, best known for its romantic theme and traditional country style.
  • C. One in a Million
    "One in a Million" is Aaliyah's influential 1996 R&B album that helped redefine the genre with its innovative production and smooth, futuristic sound.
  • D. One in a Million
    "One in a Million" is an R&B song by American singer-songwriter Ne-Yo, known for its smooth production and romantic lyrics.
  • E. Music for Millions
    Music for Millions is a 1944 American musical comedy-drama film best known for its heartwarming World War II-era story and ensemble cast, including Phillip Terry.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02970df88190a1bf35dffd131d9d completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8ea22c081909cc34f1030a8589b completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 10:13 p.m.