Triple

T14398014
Position Surface form Disambiguated ID Type / Status
Subject Multiplicity E357000 entity
Predicate cinematographyBy 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: [Multiplicity, cinematographyBy, László Kovács]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: László Kovács
Context triple: [Multiplicity, cinematographyBy, 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 Nagy
    László Nagy is a common Hungarian name shared by several notable figures, including a poet, a handball player, and a politician.
  • D. Gábor Vajna
    Gábor Vajna was a Hungarian fascist politician who served as Interior Minister in the pro-Nazi Arrow Cross regime during World War II.
  • E. László Takács
    László Takács is a Hungarian mathematician known for his contributions to probability theory and queueing theory.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9083f9d081908fe5c99655c410b3 completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a36382481909a39ba5e51084051 completed May 8, 2026, 5:52 a.m.
Created at: April 10, 2026, 1:17 a.m.