Triple

T5577011
Position Surface form Disambiguated ID Type / Status
Subject What's Love Got to Do with It E146344 entity
Predicate basedOn P98 FINISHED
Object I, Tina E250028 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: I, Tina | Statement: [What's Love Got to Do with It, basedOn, I, Tina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: I, Tina
Context triple: [What's Love Got to Do with It, basedOn, I, Tina]
  • A. I, Tina (autobiography) chosen
    "I, Tina" is the candid autobiography of legendary singer Tina Turner, chronicling her rise to fame, turbulent marriage to Ike Turner, and ultimate journey to independence and empowerment.
  • B. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • C. Tina
    Tina is a fictional character portrayed by American actress Idara Victor.
  • D. Tina
    Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
  • E. Tina
    Tina is a feminine given name commonly used in English-speaking countries, often as a diminutive of names like Christina, Martina, or Valentina.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020697fbc8190bd084d7896db3ab8 completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c02855acac8190bd00219aa9647e98 completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:37 p.m.