Triple

T15300630
Position Surface form Disambiguated ID Type / Status
Subject Love Is Where It Falls E365776 entity
Predicate title P38 FINISHED
Object Love Is Where It Falls E365776 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: Love Is Where It Falls | Statement: [Love Is Where It Falls, title, Love Is Where It Falls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Love Is Where It Falls
Context triple: [Love Is Where It Falls, title, Love Is Where It Falls]
  • A. Love Is Where It Falls chosen
    Love Is Where It Falls is a memoir by British actor and director Simon Callow reflecting on his intense, complex relationship with theatrical agent Peggy Ramsay.
  • B. Fall in Love
    "Fall in Love" is a popular Afrobeat love song by Nigerian artist D'banj that became one of his signature hits across Africa.
  • C. Fall in Love
    "Fall in Love" is a breakout hip-hop/R&B single by American rapper GoldLink that showcases his melodic flow over a danceable, groove-driven production.
  • D. Fall in Love
    "Fall in Love" is a notable creative work by Bangalee, likely recognized as one of the artist's prominent releases.
  • E. Fall in Love
    "Fall in Love" is an episode of the American sitcom *The King of Queens*, featuring the comedic misadventures of Doug and Carrie Heffernan in Queens, New York.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0368869f8819098cf9e7801e37548 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef8513a08190b2d2a7dde85dd43d completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:15 a.m.