Triple

T13988775
Position Surface form Disambiguated ID Type / Status
Subject A Face in the Crowd E336511 entity
Predicate character P662 FINISHED
Object Marcia Jeffries E622402 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: Marcia Jeffries | Statement: [A Face in the Crowd, character, Marcia Jeffries]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marcia Jeffries
Context triple: [A Face in the Crowd, character, Marcia Jeffries]
  • A. June Jordan
    June Jordan was an influential African American poet, essayist, and activist whose work powerfully addressed race, gender, social justice, and Black liberation.
  • B. Barbara Smith
    Barbara Smith is an influential Black feminist scholar, activist, and writer who co-founded the Combahee River Collective and helped shape contemporary intersectional feminist thought.
  • C. Barbara Smith
    Barbara Smith is the wife of Benjamin A. Smith II, a former United States Senator from Massachusetts and close associate of the Kennedy family.
  • D. Beverly Franklin
    Beverly Franklin is a person notable enough to be recognized as a significant bearer of the surname Franklin.
  • E. Nella Walker chosen
    Nella Walker was an American character actress active in the early to mid-20th century, known for her supporting roles in numerous Hollywood films.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea537408190bb9d35963886803f completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac9604cc819088cde0ad8271ad48 completed May 6, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:18 p.m.