Triple

T8137871
Position Surface form Disambiguated ID Type / Status
Subject Cesar E190016 entity
Predicate hasVariant P455 FINISHED
Object César E36329 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: César | Statement: [Cesar, hasVariant, César]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: César
Context triple: [Cesar, hasVariant, César]
  • A. César chosen
    César is a masculine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries and derived from the Roman family name Caesar.
  • B. César
    César is a French film written and directed by Marcel Pagnol, forming the final part of his renowned Marseille trilogy.
  • C. Giulio Cesare
    Giulio Cesare is a celebrated Baroque opera by George Frideric Handel, renowned for its virtuosic arias and dramatic portrayal of Julius Caesar’s encounter with Cleopatra.
  • D. Giulio Cesare
    Giulio Cesare was an Italian Conte di Cavour–class battleship that served in the Regia Marina during both World Wars before later being transferred to the Soviet Navy as war reparations.
  • E. Cesare
    Cesare is the somnambulist character from the classic 1920 German Expressionist horror film "The Cabinet of Dr. Caligari."
  • 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_69ca82bd9900819099477cdc2eb4244f completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4402b35c81909363ffa9ce952ca4 completed March 31, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde71b7688819096b2d30a37a8a00b completed April 2, 2026, 3:48 a.m.
Created at: March 30, 2026, 5:35 p.m.