Triple

T9766004
Position Surface form Disambiguated ID Type / Status
Subject Laura Ricketts E236991 entity
Predicate sibling P363 FINISHED
Object Pete Ricketts E76083 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: Pete Ricketts | Statement: [Laura Ricketts, sibling, Pete Ricketts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pete Ricketts
Context triple: [Laura Ricketts, sibling, Pete Ricketts]
  • A. Pete Ricketts chosen
    Pete Ricketts is an American businessman and Republican politician who served as the governor of Nebraska and later as a U.S. senator from the state.
  • B. Ben Sasse
    Ben Sasse is an American academic and politician who served as a U.S. Senator from Nebraska before becoming president of the University of Florida.
  • C. Nick Thune
    Nick Thune is an American stand-up comedian and actor known for his dry, absurdist humor and appearances in film and television.
  • D. Sam Brownback
    Sam Brownback is an American Republican politician and former governor of Kansas who also served in both the U.S. House of Representatives and the U.S. Senate.
  • E. Roy Blunt
    Roy Blunt is an American Republican politician who served in the U.S. House of Representatives and later as a U.S. Senator from Missouri, holding several key leadership roles in Congress.
  • 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_69ca84d831b8819090322686b47887ce completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda0a040988190b1c940f9e5c42f9c completed April 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcf965e88190b505ce160f77e9b7 completed April 5, 2026, 1:38 a.m.
Created at: March 30, 2026, 8:25 p.m.