Triple

T14938839
Position Surface form Disambiguated ID Type / Status
Subject Parfumerie E372467 entity
Predicate author P4 FINISHED
Object Miklós László E533748 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: Miklós László | Statement: [Parfumerie, author, Miklós László]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miklós László
Context triple: [Parfumerie, author, Miklós László]
  • A. Miklós László chosen
    Miklós László was a Hungarian-born playwright best known for writing the stage play that inspired the classic film "The Shop Around the Corner."
  • B. László Szabó
    László Szabó is a Hungarian-born French actor and filmmaker known for his work in European art cinema, including collaborations with directors of the French New Wave.
  • C. Miklós Lázár
    Miklós Lázár is an actor known for his role in the supernatural crime thriller film "The First Power."
  • D. Béla Miklós
    Béla Miklós was a Hungarian military officer and politician who served as Prime Minister of Hungary near the end of World War II and played a key role in the country’s transition away from Nazi Germany.
  • E. Imre Molnár
    Imre Molnár is the pseudonym of Imre Lakatos, a prominent Hungarian-born philosopher of mathematics and science known for his work on the methodology of scientific research programmes.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64904d88190b6b4140da8e8199d completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff133571008190b7e7867208095b90 completed May 9, 2026, 10:57 a.m.
Created at: April 10, 2026, 2:38 a.m.