Triple

T11202689
Position Surface form Disambiguated ID Type / Status
Subject Gloria (1980 film) E265077 entity
Predicate influenced P9 FINISHED
Object Leon (1994 film) E247495 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: Leon (1994 film) | Statement: [Gloria (1980 film), influenced, Leon (1994 film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leon (1994 film)
Context triple: [Gloria (1980 film), influenced, Leon (1994 film)]
  • A. Léon: The Professional chosen
    Léon: The Professional is a 1994 crime thriller film by Luc Besson about a hitman who forms an unusual bond with a young girl after her family is murdered.
  • B. Léon
    Léon is a masculine given name of French origin, commonly used in French-speaking countries and derived from the Latin name Leo, meaning "lion."
  • C. Léon
    Léon is a traditional cultural and historical region in northwestern Brittany, France, known for its distinct Breton heritage and coastal landscapes.
  • D. Léon
    Léon is a French surname borne by various notable individuals across fields such as politics, arts, and academia.
  • E. Di Lenarda
    Di Lenarda is an Italian surname, notably borne by individuals such as Roberto Di Lenarda.
  • 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_69d6aa9eb9248190b20211772621b4bc completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8c36c188190bfa4d5f8e6cbbbea completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4971d537c8190ab53a2ca18d643f3 completed April 19, 2026, 8:49 a.m.
Created at: April 8, 2026, 9:29 p.m.