Triple

T13647082
Position Surface form Disambiguated ID Type / Status
Subject Larz Anderson Park E326130 entity
Predicate namedAfter P63 FINISHED
Object Larz Anderson E657431 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: Larz Anderson | Statement: [Larz Anderson Park, namedAfter, Larz Anderson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larz Anderson
Context triple: [Larz Anderson Park, namedAfter, Larz Anderson]
  • A. Larz Anderson chosen
    Larz Anderson was a wealthy American diplomat and socialite from Boston, known for his extensive automobile collection and philanthropic legacy.
  • B. Elwood Bredell
    Elwood Bredell was an American cinematographer best known for his work on classic Hollywood films and film noir in the 1930s and 1940s.
  • C. Alvin Marks
    Alvin Marks was an American inventor known for his work on advanced energy technologies and high-efficiency lighting concepts.
  • D. Fred Fisher
    Fred Fisher was an American automobile-body manufacturer and entrepreneur best known as a co-founder of the Fisher Body Company, which became a major supplier to General Motors.
  • E. Jerry Wald
    Jerry Wald was an American film producer and screenwriter known for his influential work in Hollywood during the 1930s–1950s, including several acclaimed dramas and film noirs.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc6073e888190965456a639839749 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78af948408190bca7f2e46863391e completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:52 p.m.