Triple

T17030188
Position Surface form Disambiguated ID Type / Status
Subject Gilbert Bécaud E413172 entity
Predicate wroteSong P2831 FINISHED
Object Dimanche à Orly E1246905 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: Dimanche à Orly | Statement: [Gilbert Bécaud, wroteSong, Dimanche à Orly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dimanche à Orly
Context triple: [Gilbert Bécaud, wroteSong, Dimanche à Orly]
  • A. Dimanche à Orly chosen
    Dimanche à Orly is a popular French chanson by singer-songwriter Gilbert Bécaud that nostalgically evokes the atmosphere of Paris’s Orly Airport on a Sunday.
  • B. Le Parisien
    Le Parisien is a major French daily newspaper known for its coverage of national and local news, sports, and culture, particularly in the Paris region.
  • C. Les Parisiens
    Les Parisiens is a French drama film that follows the intersecting lives and emotional struggles of various characters in contemporary Paris.
  • D. Les Parisiens
    Les Parisiens is the widely used French nickname for Paris Saint-Germain Football Club and its players, emphasizing their identity as representatives of Paris.
  • E. Sous le ciel de Paris
    Sous le ciel de Paris is a classic French chanson, famously interpreted by Juliette Gréco, that evokes the romantic and poetic atmosphere of 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_69d886cd18288190b006abab23f811b7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d918ec8190b54c40c2a5e9b6b9 completed April 18, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012336cfd481909f93c6ea7c94b49f completed May 11, 2026, 12:30 a.m.
Created at: April 10, 2026, 5:33 a.m.