Triple

T20534928
Position Surface form Disambiguated ID Type / Status
Subject Will Young E504168 entity
Predicate notableSingle P3283 FINISHED
Object Evergreen NE NERFINISHED

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: Evergreen | Statement: [Will Young, notableSingle, Evergreen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Evergreen
Context triple: [Will Young, notableSingle, Evergreen]
  • A. Evergreen
    Evergreen is a literary imprint known for publishing innovative and influential works, particularly in avant-garde and progressive literature.
  • B. Evergreen
    Evergreen is a small city in southern Alabama that serves as the administrative and commercial center of Conecuh County.
  • C. Evergreen chosen
    Evergreen is a 1934 British musical film directed by Victor Saville, known for its blend of romance, comedy, and popular songs of the era.
  • D. Evergreen
    Evergreen is a Christmas-themed studio album by the a cappella group Pentatonix, featuring vocal arrangements of classic and contemporary holiday songs.
  • E. Evergreen Extension
    Evergreen Extension is a rapid transit extension of Metro Vancouver’s SkyTrain system that expanded the Millennium Line service into the Tri-Cities area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b476648190bc6019622ae54d3c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a06df04081908fa95c6214f06093 completed April 20, 2026, 9:53 p.m.
Created at: April 16, 2026, 11:37 a.m.