Triple

T19672031
Position Surface form Disambiguated ID Type / Status
Subject In a World Like This E472355 entity
Predicate hasPart P35 FINISHED
Object Madeleine NE NERFINISHED

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: Madeleine | Statement: [In a World Like This, hasPart, Madeleine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madeleine
Context triple: [In a World Like This, hasPart, Madeleine]
  • A. Madeleine chosen
    Madeleine is a feminine given name, commonly used in French and English, derived from Magdalene and often associated with literary and cultural figures.
  • B. Madeleine
    Madeleine is a Paris Métro station in central Paris that serves as an interchange between several metro lines, including the automated Line 14.
  • C. Madeleine
    "Madeleine" is a 1950 British crime drama film directed by David Lean and starring Ann Todd, based on the true story of a 19th-century Glasgow woman accused of poisoning her lover.
  • D. Madeleine de Beaupre
    Madeleine de Beaupre is the central female protagonist of the 1936 romantic comedy film "Desire," portrayed as a sophisticated jewel thief whose schemes become entangled with an unsuspecting American engineer.
  • E. Louisette
    Louisette is the given name of Louisette Bertholle, a French chef and co-author of the influential cookbook "Mastering the Art of French Cooking."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6416cb0bc8190ab27dd28eebb50e7 completed April 20, 2026, 3:08 p.m.
Created at: April 10, 2026, 1:45 p.m.