Triple

T10740158
Position Surface form Disambiguated ID Type / Status
Subject Sean Flynn E253300 entity
Predicate workedFor P1910 FINISHED
Object Paris Match E861132 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: Paris Match | Statement: [Sean Flynn, workedFor, Paris Match]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris Match
Context triple: [Sean Flynn, workedFor, Paris Match]
  • A. Paris Match chosen
    Paris Match is a major French weekly news and celebrity magazine known for its photojournalism and coverage of politics, culture, and public figures.
  • B. La Parisienne
    La Parisienne is a vibrant Fauvist portrait painting by Dutch-French artist Kees van Dongen, celebrated for its bold colors and depiction of fashionable Parisian modernity.
  • C. La Ville Rose
    La Ville Rose is the affectionate nickname for the French city of Toulouse, referencing its distinctive pink-hued brick architecture.
  • D. Count of Paris
    Count of Paris was a powerful medieval noble title associated with the rulers of the Paris region, notably held by Hugh Capet before he became king of France and founded the Capetian dynasty.
  • E. 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.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d71043106c819091939950f532eda5 completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69de22ed6edc8190beb76bd2971c7cec completed April 14, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:14 p.m.