Triple

T9759684
Position Surface form Disambiguated ID Type / Status
Subject Is Paris Burning? E236637 entity
Predicate originalTitle P65 FINISHED
Object Paris brûle-t-il ? E236637 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 brûle-t-il ? | Statement: [Is Paris Burning?, originalTitle, Paris brûle-t-il ?]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris brûle-t-il ?
Context triple: [Is Paris Burning?, originalTitle, Paris brûle-t-il ?]
  • A. Is Paris Burning? chosen
    "Is Paris Burning?" is a 1966 historical war film depicting the liberation of Paris during World War II, based on the book by Larry Collins and Dominique Lapierre.
  • B. Paris 3
    Paris 3 is a French public university in Paris, known for its focus on humanities, languages, arts, and social sciences as part of the Sorbonne university group.
  • C. Paris en colère
    "Paris en colère" is a famous French song performed by Mireille Mathieu, known for its emotional portrayal of Paris’s spirit and resilience.
  • D. Paris Qualles
    Paris Qualles is an American television and film screenwriter and producer known for his work on socially conscious dramas and biographical projects.
  • E. Paris Bar
    The Paris Bar is the professional association and regulatory body for lawyers practicing in Paris, France.
  • 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_69ca84d64f6c8190a4ed4e9f5936eda5 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda049995c81908569ec61805642b2 completed April 1, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcdbdbcc8190b2c454729a50f7fb completed April 5, 2026, 1:37 a.m.
Created at: March 30, 2026, 8:24 p.m.