Triple

T12907140
Position Surface form Disambiguated ID Type / Status
Subject Pump E308755 entity
Predicate mainSongwriter P1141 FINISHED
Object Holly Knight E733314 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: Holly Knight | Statement: [Pump, mainSongwriter, Holly Knight]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holly Knight
Context triple: [Pump, mainSongwriter, Holly Knight]
  • A. Holly Knight chosen
    Holly Knight is an American songwriter and musician renowned for penning numerous 1980s rock and pop hits for artists such as Tina Turner, Pat Benatar, and Heart.
  • B. Shirley Mitchell
    Shirley Mitchell was an American character actress best known for her comedic roles in classic radio and television shows such as "I Love Lucy."
  • C. Betsy Garth
    Betsy Garth is a central character in the Western television series "The Virginian," known for her close connection to the Shiloh Ranch and its core cast.
  • D. Sandy Owens
    Sandy Owens is a central character in the 1950 Western film "Wagon Master," portrayed as one of the key figures in the story of a wagon train journey across the American frontier.
  • E. Donna Dixon
    Donna Dixon is an American actress and former model known for her roles in 1980s comedies and for her long career in film and television.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9719d4d1c8190a2c4f362e1772a73 completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a565ce508190a73f33708e61dc7d completed May 3, 2026, 1:31 a.m.
Created at: April 9, 2026, 5:41 p.m.