Triple

T23191998
Position Surface form Disambiguated ID Type / Status
Subject Love, Marriage & Divorce E579766 entity
Predicate hasPart P35 FINISHED
Object Take It Back 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 It Back | Statement: [Love, Marriage & Divorce, hasPart, Take It Back]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Take It Back
Context triple: [Love, Marriage & Divorce, hasPart, Take It Back]
  • A. Take It Back
    Take It Back is a gripping legal thriller novel by British author Kia Abdullah that explores themes of prejudice, sexual assault, and the pursuit of justice through a high-stakes courtroom drama.
  • B. Take It Back chosen
    "Take It Back" is a song featured on the collaborative R&B album "Love, Marriage & Divorce" by Toni Braxton and Babyface.
  • C. Take It Back
    "Take It Back" is a song by the Wu-Tang Clan, released as a single from their 2007 studio album "8 Diagrams."
  • D. Take It Back
    "Take It Back" is a song by Norah Jones from her 2012 album *Little Broken Hearts*, blending her signature mellow vocals with atmospheric, indie-pop production.
  • E. Take It Back
    "Take It Back" is a track by Blondie featured on their 2014 album Ghosts of Download, blending the band's classic pop-rock sensibilities with contemporary electronic influences.
  • 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_69e24600eed08190bd7e5295653a1503 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18fd86640819092308751d23c6642 completed April 29, 2026, 4:58 a.m.
Created at: April 17, 2026, 4:06 p.m.