Triple

T19751594
Position Surface form Disambiguated ID Type / Status
Subject Ossian Sweet trial E474388 entity
Predicate hasDefendant P2238 FINISHED
Object Otis Sweet NE NERFINISHED

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: Otis Sweet | Statement: [Ossian Sweet trial, hasDefendant, Otis Sweet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Otis Sweet
Context triple: [Ossian Sweet trial, hasDefendant, Otis Sweet]
  • A. Otis Sweet chosen
    Otis Sweet was one of the African American defendants in the landmark 1925 Ossian Sweet trial, a pivotal civil rights case challenging racial housing segregation in Detroit.
  • B. Otis Brazil
    Otis Brazil is the Brazilian subsidiary of the global Otis Elevator Company, responsible for manufacturing, installing, and servicing elevators and escalators in Brazil.
  • C. Otis Burns
    Otis Burns is an individual notable enough to be specifically cited as a bearer of the surname Burns, though detailed public information about him is limited.
  • D. Otis Harlan
    Otis Harlan was an American actor and comedian best known for his early film and stage work during the silent and early sound eras.
  • E. Mahlon Sweet
    Mahlon Sweet was a prominent local aviation advocate and civic leader in Eugene, Oregon, whose efforts were instrumental in establishing the city’s municipal airport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51940a0819087bd2996f98da668 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65299a7048190a9b22307ac06bd03 completed April 20, 2026, 4:21 p.m.
Created at: April 10, 2026, 1:48 p.m.