Triple

T6385633
Position Surface form Disambiguated ID Type / Status
Subject Anytime You Need a Friend E143692 entity
Predicate musicVideoDirector P4911 FINISHED
Object Diane Martel E135700 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: Diane Martel | Statement: [Anytime You Need a Friend, musicVideoDirector, Diane Martel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diane Martel
Context triple: [Anytime You Need a Friend, musicVideoDirector, Diane Martel]
  • A. Diane Martel chosen
    Diane Martel is an American music video director and choreographer known for her work on numerous high-profile pop and R&B videos.
  • B. Judith Kilpatrick
    Judith Kilpatrick is a notable individual recognized as a prominent bearer of the surname Kilpatrick.
  • C. Maureen Beattie
    Maureen Beattie is a Scottish actress known for her extensive work in television, theatre, and film, including roles in British dramas and comedies.
  • D. Laura Deming
    Laura Deming is a venture capitalist and longevity researcher best known for founding The Longevity Fund, which invests in companies developing therapies to extend healthy human lifespan.
  • E. Melissa Sasse
    Melissa Sasse is the wife of American academic and former U.S. Senator Ben Sasse and a longtime partner in his political and professional life.
  • 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_69c008dac1ec81909cef8157ccd69962 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0686764648190864163d390db292d completed March 22, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6387dc8888190ba63efcc9aff41b2 completed March 27, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:34 p.m.