Triple

T7548570
Position Surface form Disambiguated ID Type / Status
Subject Carmen Basilio E178468 entity
Predicate wonTitleFrom P30822 FINISHED
Object Tony DeMarco E689763 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: Tony DeMarco | Statement: [Carmen Basilio, wonTitleFrom, Tony DeMarco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tony DeMarco
Context triple: [Carmen Basilio, wonTitleFrom, Tony DeMarco]
  • A. Tony DeMarco chosen
    Tony DeMarco was an American professional boxer and former world welterweight champion known for his aggressive, crowd-pleasing fighting style during the 1950s.
  • B. Tony Corrente
    Tony Corrente is an American football official best known for his long NFL refereeing career, including serving as the head referee for multiple high-profile games.
  • C. Tony Palermo
    Tony Palermo is an American drummer best known for his work with the rock band Papa Roach.
  • D. John DiFronzo
    John DiFronzo was an American mobster who rose to become a powerful boss of the Chicago Outfit and a prominent figure in organized crime.
  • E. Paul De Meo
    Paul De Meo was an American screenwriter and producer best known for co-writing action and war-themed films and television projects, often in collaboration with J. Michael Straczynski and others.
  • 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_69c69f2cbe08819088f9eb0c03ef529b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f89b9afc8190b3e61a8e2cea7ad7 completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c911608d408190b149c7c56931a18d completed March 29, 2026, 11:47 a.m.
Created at: March 27, 2026, 3:49 p.m.