Triple

T5101278
Position Surface form Disambiguated ID Type / Status
Subject CODA E114984 entity
Predicate character P662 FINISHED
Object Leo Rossi E161005 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: Leo Rossi | Statement: [CODA, character, Leo Rossi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leo Rossi
Context triple: [CODA, character, Leo Rossi]
  • A. Leo Rossi chosen
    Leo Rossi is an American character actor known for his supporting roles in crime dramas and thrillers in film and television.
  • B. Guido De Rosso
    Guido De Rosso is an Italian former professional road cyclist known for his strong stage-race performances in the early 1960s.
  • C. Leo Benvenuti
    Leo Benvenuti is an American screenwriter best known for co-writing popular family comedies such as "The Santa Clause" and "Kicking & Screaming."
  • D. Marco Barricelli
    Marco Barricelli is an Italian-American actor and theatre director known for his work on stage and in voice roles for film and television.
  • E. Enzo Scifo
    Enzo Scifo is a former Belgian attacking midfielder renowned for his playmaking skills and influential performances for both the Belgian national team and top European clubs in the 1980s and 1990s.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7584ed408190a6d1086588f24faa completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfcb931f908190b72d825b95ae4861 completed March 22, 2026, 10:59 a.m.
Created at: March 20, 2026, 1:40 p.m.