Triple

T13777195
Position Surface form Disambiguated ID Type / Status
Subject Leonard Harris E331039 entity
Predicate name P16 FINISHED
Object Leonard Harris E331039 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: Leonard Harris | Statement: [Leonard Harris, name, Leonard Harris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonard Harris
Context triple: [Leonard Harris, name, Leonard Harris]
  • A. Leonard Harris chosen
    Leonard Harris is an American actor and former television news commentator best known for his role as Senator Charles Palantine in the film "Taxi Driver."
  • B. Leonard Henderson
    Leonard Henderson was an influential North Carolina jurist and public figure after whom the city of Hendersonville was named.
  • C. Leonard Johnson
    Leonard Johnson is an American former NFL cornerback who played for multiple teams after entering the league as an undrafted free agent.
  • D. Leonard Rogers
    Leonard Rogers was a prominent British physician and researcher in tropical medicine, particularly known for his work in India on cholera, dysentery, and kala-azar.
  • E. Elmer Blaney Harris
    Elmer Blaney Harris was an American playwright and author best known for writing the stage play "Johnny Belinda," which was later adapted into the acclaimed 1948 film.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0238bdbc8190a946e6e5431632a5 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0e152ac8190b8d705295df4834a completed May 3, 2026, 9:40 p.m.
Created at: April 9, 2026, 10:10 p.m.