Triple

T10524035
Position Surface form Disambiguated ID Type / Status
Subject Betty Blue E248249 entity
Predicate hasOriginalTitle P38 FINISHED
Object 37°2 le matin E869314 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: 37°2 le matin | Statement: [Betty Blue, hasOriginalTitle, 37°2 le matin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 37°2 le matin
Context triple: [Betty Blue, hasOriginalTitle, 37°2 le matin]
  • A. 37°2 le matin chosen
    37°2 le matin is a 1985 French novel by Philippe Djian, best known internationally as the source material for the film "Betty Blue."
  • B. Encore un matin
    "Encore un matin" is a popular French pop song by singer-songwriter Jean-Jacques Goldman, known for its reflective lyrics and melodic, radio-friendly style.
  • C. Serres chaudes
    Serres chaudes is a symbolist poetry collection by Belgian writer Maurice Maeterlinck, noted for its introspective, dreamlike atmosphere and exploration of psychological and spiritual states.
  • D. Demain, dès l’aube
    "Demain, dès l’aube" is a famous poem by Victor Hugo, known for its poignant evocation of grief and a solitary journey to a loved one’s grave.
  • E. Petit à petit
    Petit à petit is a 1970 ethnographic comedy film by Jean Rouch that satirically explores cultural differences through the story of Nigerien businessmen investigating life in Paris.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509e155b08190996325bf484ec55d completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d933f2d9e48190a4c5d5d5bdc0d7d8 completed April 10, 2026, 5:31 p.m.
Created at: April 6, 2026, 12:29 p.m.