Triple

T256936
Position Surface form Disambiguated ID Type / Status
Subject Marie Mosquini E5455 entity
Predicate name P16 FINISHED
Object Marie Mosquini E5455 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: Marie Mosquini | Statement: [Marie Mosquini, name, Marie Mosquini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marie Mosquini
Context triple: [Marie Mosquini, name, Marie Mosquini]
  • A. Marie Mosquini chosen
    Marie Mosquini was an American silent film actress best known for her work in Hal Roach comedies during the 1910s and 1920s.
  • B. Esther Ross
    Esther Ross was the woman who served as the sponsor and ceremonial namesake figure for the U.S. Navy battleship USS Arizona (BB-39) at its christening.
  • C. Betty Garde
    Betty Garde was an American stage, film, and radio actress known for her versatile character roles in mid-20th-century theater and entertainment.
  • D. Marie Krackowizer
    Marie Krackowizer was the wife of pioneering anthropologist Franz Boas and a supportive partner in his academic and intellectual life.
  • E. Maxine Singer
    Maxine Singer is an American molecular biologist renowned for her pioneering work in genetics and for her leadership in shaping ethical guidelines for recombinant DNA research.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d5884c88190a349d7593b688921 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3cafbcc10819083680d9a24fe2a2b completed March 1, 2026, 5:13 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.