Triple

T3864073
Position Surface form Disambiguated ID Type / Status
Subject Maya Angelou E91806 entity
Predicate wrote P2831 FINISHED
Object Mom & Me & Mom E395445 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: Mom & Me & Mom | Statement: [Maya Angelou, wrote, Mom & Me & Mom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mom & Me & Mom
Context triple: [Maya Angelou, wrote, Mom & Me & Mom]
  • A. Mom & Me & Mom chosen
    Mom & Me & Mom is a memoir by Maya Angelou that explores her complex, evolving relationship with her mother and the impact it had on her life and identity.
  • B. Same Mother
    Same Mother is a jazz album by American pianist and composer Jason Moran that blends avant-garde improvisation with blues and traditional influences.
  • C. Mom + Pop
    Mom + Pop is a song by the American rock band Lucius, known for its lush harmonies and indie-pop sensibility.
  • D. Four Mothers
    Four Mothers is a 1941 American drama film that continues the story of the Lemp family introduced in Four Daughters and its first sequel, Four Wives.
  • E. Mama
    "Mama" is a 1987 debut novel by Terry McMillan that follows a resilient Black single mother struggling to raise her children and rebuild her life amid poverty and personal turmoil.
  • 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_69aed9645f348190a9868e7cef56ab7e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec3871d881909c6c8e6d08203801 completed March 9, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c808c808190928bf07788ad9657 completed March 14, 2026, 8:29 a.m.
Created at: March 9, 2026, 3:19 p.m.