Triple

T5934736
Position Surface form Disambiguated ID Type / Status
Subject Giulio Cesare E132015 entity
Predicate featuresCharacter P626 FINISHED
Object Cornelia E162833 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: Cornelia | Statement: [Giulio Cesare, featuresCharacter, Cornelia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cornelia
Context triple: [Giulio Cesare, featuresCharacter, Cornelia]
  • A. Cornelia chosen
    Cornelia is a feminine given name of Latin origin, historically associated with several notable women in European history.
  • B. Lollia
    Lollia was the family name (nomen) of the ancient Roman gens Lollia, to which the noblewoman Lollia Paulina belonged.
  • C. Iulia
    Iulia is a Latin given name, historically used in ancient Rome and closely associated with the feminine form of the name Julius.
  • D. Leonessa
    Leonessa is a historic mountain town in central Italy, known for its medieval architecture and scenic location in the Apennines.
  • E. Julia Livilla
    Julia Livilla was a Roman imperial princess of the Julio-Claudian dynasty, known as the sister of Emperor Caligula and for her involvement in the turbulent politics of the early Roman Empire.
  • 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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c038a0c4e481908170d615330edb1a completed March 22, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3b68a1c81908a219ffee8300e02 completed March 23, 2026, 6:54 a.m.
Created at: March 22, 2026, 4 p.m.