Triple

T18093230
Position Surface form Disambiguated ID Type / Status
Subject Real Gone E433022 entity
Predicate previousWork P9710 FINISHED
Object Blood Money 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: Blood Money | Statement: [Real Gone, previousWork, Blood Money]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blood Money
Context triple: [Real Gone, previousWork, Blood Money]
  • A. Blood Money chosen
    Blood Money is a dark, theatrical 2002 album by Tom Waits, known for its cabaret-style songs and lyrics drawn from the play "Woyzeck."
  • B. Blood Money
    Blood Money is a 2006 studio album by Queensbridge hip-hop duo Mobb Deep, known for its gritty street narratives and as their first release under G-Unit Records.
  • C. Bloodmoney
    Bloodmoney is a political thriller novel by David Ignatius that delves into the murky world of CIA operations, drone warfare, and the unintended consequences of covert intelligence work.
  • D. The Big Money
    The Big Money is a 1958 British crime comedy film in which Jennifer Jayne appears alongside Ian Carmichael and Belinda Lee.
  • E. The Big Money
    The Big Money is a 1936 novel by John Dos Passos, best known as the third volume of his U.S.A. trilogy, which critiques American capitalism and society in the early 20th century through experimental narrative techniques.
  • 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dd1a75048190924ebc01da83851b completed April 19, 2026, 1:48 p.m.
Created at: April 10, 2026, 10:27 a.m.