Triple

T6806258
Position Surface form Disambiguated ID Type / Status
Subject Luther Allison E156312 entity
Predicate associatedAct P37 FINISHED
Object Magic Sam E143524 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: Magic Sam | Statement: [Luther Allison, associatedAct, Magic Sam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magic Sam
Context triple: [Luther Allison, associatedAct, Magic Sam]
  • A. Magic Sam chosen
    Magic Sam was an influential American Chicago blues guitarist and singer known for his soulful vocals, stinging guitar tone, and modern West Side sound.
  • B. Moses the Black
    Moses the Black was a 4th-century Ethiopian desert monk and former bandit who became a renowned Christian ascetic and saint among the Desert Fathers.
  • C. Dedi the magician
    Dedi the magician is a legendary ancient Egyptian wonder-worker featured in the Westcar Papyrus, famed for performing miraculous feats such as reattaching severed heads.
  • D. Magic Slim
    Magic Slim was an American Chicago blues guitarist and singer renowned for his raw, electrifying style and influential recordings with his band the Teardrops.
  • E. Roc the Panther
    Roc the Panther is the costumed panther mascot representing the University of Pittsburgh at its athletic events and campus activities.
  • 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_69c68826e6a48190a3d220b541e639de completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d3082dcc8190a84bc056236cc52e completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723d525bc8190aaf2390d690dc6a6 completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:16 p.m.