Triple

T12565524
Position Surface form Disambiguated ID Type / Status
Subject Larry Semon E295467 entity
Predicate name P16 FINISHED
Object Larry Semon E295467 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: Larry Semon | Statement: [Larry Semon, name, Larry Semon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larry Semon
Context triple: [Larry Semon, name, Larry Semon]
  • A. Larry Semon chosen
    Larry Semon was a prominent American silent film comedian, director, and actor known for his energetic slapstick shorts in the 1910s and 1920s.
  • B. Roscoe Karns
    Roscoe Karns was an American character actor known for his fast-talking, wisecracking roles in classic Hollywood films of the 1930s and 1940s.
  • C. James F. Sennett
    James F. Sennett is a philosopher of religion known for his work in analytic theism and for editing influential scholarly collections in that field.
  • D. Edward John Woods
    Edward John Woods was a prominent 19th-century architect in South Australia known for designing significant public and civic buildings.
  • E. Ricardo Cortez
    Ricardo Cortez was an American actor of the silent and early sound film era, best known for his leading-man roles in crime dramas and early film noir.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9549611c081909e611756f3cce7f0 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6558f87b081909ba179b49bae3913 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 11:49 p.m.