Triple

T12681040
Position Surface form Disambiguated ID Type / Status
Subject Carlo Caneva E302946 entity
Predicate name P16 FINISHED
Object Carlo Caneva E302946 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: Carlo Caneva | Statement: [Carlo Caneva, name, Carlo Caneva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carlo Caneva
Context triple: [Carlo Caneva, name, Carlo Caneva]
  • A. Carlo Caneva chosen
    Carlo Caneva was an Italian general best known for commanding Italy’s expeditionary forces during the Italo-Turkish War in Libya.
  • B. Federico Zandomeneghi
    Federico Zandomeneghi was an Italian painter associated with the Impressionist movement, known for his intimate domestic scenes and portraits, particularly of women.
  • C. Simon Ammann
    Simon Ammann is a Swiss ski jumper and multiple Olympic champion renowned for his dominance in the sport during the early 2000s.
  • D. Andrea Antonelli
    Andrea Antonelli was an Italian motorcycle road racer who competed in the Supersport World Championship before his career was tragically cut short by a fatal racing accident in 2013.
  • E. Juan Pistarini
    Juan Pistarini was an Argentine military officer and politician who served as Minister of Public Works and played a key role in developing Argentina’s infrastructure in the mid-20th century.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b32dbc81908101fc5f07e26ed3 completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671a54b008190b02f9585d6c6ff77 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:21 p.m.