Triple

T18149999
Position Surface form Disambiguated ID Type / Status
Subject Emeli Sandé E434478 entity
Predicate notableCollaboration P8554 FINISHED
Object Professor Green 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: Professor Green | Statement: [Emeli Sandé, notableCollaboration, Professor Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Professor Green
Context triple: [Emeli Sandé, notableCollaboration, Professor Green]
  • A. Professor Green chosen
    Professor Green is a British rapper and songwriter known for his witty lyricism, chart-topping singles, and appearances on UK television.
  • B. Dr. Green
    Dr. Green is a minor supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
  • C. Dr. Greenthumb
    "Dr. Greenthumb" is a popular 1998 hip-hop song by Cypress Hill, known for its humorous, cannabis-themed lyrics and distinctive persona created by rapper B-Real.
  • D. Professor Fig
    Professor Fig is a wise and supportive Hogwarts professor in the video game "Hogwarts Legacy" who mentors the player character through their magical journey and the central mystery of the story.
  • E. Frank Greene
    Frank Greene is an American jazz and studio trumpeter best known for his work as a member of the CBS Orchestra on the "Late Show with David Letterman."
  • 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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de3812e8819097f025476d5c6a1d completed April 19, 2026, 1:52 p.m.
Created at: April 10, 2026, 10:29 a.m.