Triple

T22092592
Position Surface form Disambiguated ID Type / Status
Subject Rent: Live E545945 entity
Predicate featuresSong P2152 FINISHED
Object Take Me or Leave Me 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: Take Me or Leave Me | Statement: [Rent: Live, featuresSong, Take Me or Leave Me]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Take Me or Leave Me
Context triple: [Rent: Live, featuresSong, Take Me or Leave Me]
  • A. Take Me or Leave Me chosen
    "Take Me or Leave Me" is a powerful duet from the musical Rent in which the characters Maureen and Joanne confront the tensions in their tumultuous relationship.
  • B. Take Me as I Am (Or Let Me Go)
    "Take Me as I Am (Or Let Me Go)" is a country song written and recorded by American singer-songwriter Ray Price, known as one of his early hits that helped establish his traditional honky-tonk style.
  • C. Love Me or Leave Me
    Love Me or Leave Me is a popular song closely associated with American singer Ruth Etting, becoming one of her signature hits in the 1920s.
  • D. Take Me, Take Me With You
    "Take Me, Take Me With You" is a novel by Lauren Kelly, a pseudonym of Joyce Carol Oates, blending psychological suspense with dark, character-driven drama.
  • E. Take Me
    "Take Me" is a 2017 dark comedy film about a struggling entrepreneur who runs a simulated kidnapping service that spirals out of control when he takes on an unusually mysterious client.
  • 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e6b1d881909bf0f4a52199354c completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.