Triple

T23411117
Position Surface form Disambiguated ID Type / Status
Subject The Truth E560068 entity
Predicate featuresArtist P1952 FINISHED
Object Beanie Mac E1585329 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: Beanie Mac | Statement: [The Truth, featuresArtist, Beanie Mac]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beanie Mac
Context triple: [The Truth, featuresArtist, Beanie Mac]
  • A. Beanie Mac chosen
    Beanie Mac is a hip-hop artist known for contributing a featured verse to the track "The Truth."
  • B. Beanie Sigel
    Beanie Sigel is an American rapper and actor from Philadelphia known for his gritty lyricism and work with Roc-A-Fella Records.
  • C. Beanie (Mack Bitch)
    "Beanie (Mack Bitch)" is a hip-hop track by rapper Beanie Sigel, known for its gritty lyrics and street-oriented themes.
  • D. Fifi Macaffee
    Fifi Macaffee is a character portrayed by Australian actor Roger Ward, best known from the cult action film "The Cars That Ate Paris."
  • E. Meg Steedle
    Meg Steedle is an American actress known for her work in television dramas and comedies, including prominent roles on series such as Boardwalk Empire and The Mysteries of Laura.
  • 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_69e2454b3a5881909c64773dc8a5d289 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a51183bc8190bd4860607b26b4b2 completed April 29, 2026, 6:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c8243ada081908ff5312f06b3a465 completed May 19, 2026, 3:31 p.m.
Created at: April 17, 2026, 5:38 p.m.