Triple

T7548569
Position Surface form Disambiguated ID Type / Status
Subject Carmen Basilio E178468 entity
Predicate notableOpponent P893 FINISHED
Object Gene Fullmer E643847 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: Gene Fullmer | Statement: [Carmen Basilio, notableOpponent, Gene Fullmer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gene Fullmer
Context triple: [Carmen Basilio, notableOpponent, Gene Fullmer]
  • A. Gene Fullmer chosen
    Gene Fullmer was an American middleweight boxing champion of the 1950s and 1960s known for his rugged, aggressive style and notable bouts with Sugar Ray Robinson.
  • B. Jeffrey Fuller
    Jeffrey Fuller is known primarily as the son of prominent American lawyer, feminist, and civil liberties advocate Crystal Eastman.
  • C. Dale Fuller
    Dale Fuller is a technology executive best known for leading software companies such as Borland during pivotal periods of restructuring and product strategy.
  • D. Jerry Fuller
    Jerry Fuller is an American songwriter and record producer best known for crafting numerous pop and country hits in the 1960s and 1970s.
  • E. Greg Stillson
    Greg Stillson is the ambitious, populist politician and primary antagonist in Stephen King’s novel "The Dead Zone," whose rise to power is foreseen to lead to catastrophic consequences.
  • 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_69c856bb83b88190947c0efed84b891a completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:49 p.m.