Triple

T3757589
Position Surface form Disambiguated ID Type / Status
Subject The King of Marvin Gardens E82084 entity
Predicate cinematographer P1953 FINISHED
Object László Kovács E260960 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: László Kovács | Statement: [The King of Marvin Gardens, cinematographer, László Kovács]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: László Kovács
Context triple: [The King of Marvin Gardens, cinematographer, László Kovács]
  • A. László Kovács chosen
    László Kovács was a renowned Hungarian-American cinematographer celebrated for his influential work in New Hollywood cinema, including landmark films of the late 1960s and 1970s.
  • B. László Papp
    László Papp was a legendary Hungarian boxer who became the first boxer to win three consecutive Olympic gold medals.
  • C. László Bárdossy
    László Bárdossy was a Hungarian politician who served as prime minister during World War II and played a key role in aligning Hungary with Nazi Germany.
  • D. László Csatay
    László Csatay was a Hungarian military officer and politician who served as Hungary’s Minister of Defence during World War II.
  • E. Lajos Pósa
    Lajos Pósa is a Hungarian mathematician known for his contributions to combinatorics and graph theory, as well as for his influential work in mathematics education.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbc04d348190b0e4a90d18bdd160 completed March 8, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c6b2a488190a621cc223c673615 completed March 14, 2026, 8:29 a.m.
Created at: March 8, 2026, 3:35 p.m.