Triple

T5546196
Position Surface form Disambiguated ID Type / Status
Subject Richard Schweiker E145413 entity
Predicate familyName P18 FINISHED
Object Schweiker E167164 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: Schweiker | Statement: [Richard Schweiker, familyName, Schweiker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schweiker
Context triple: [Richard Schweiker, familyName, Schweiker]
  • A. Mark Schweiker chosen
    Mark Schweiker is an American politician who served as the 44th governor of Pennsylvania in the early 2000s.
  • B. Mick Mulvaney
    Mick Mulvaney is an American politician and former U.S. Representative who served in the Trump administration in senior roles, including as acting White House Chief of Staff and Director of the Office of Management and Budget.
  • C. Chad Wolf
    Chad Wolf is an American government official who served as acting Secretary of Homeland Security under President Donald Trump.
  • D. Ryan Zinke
    Ryan Zinke is an American politician and former U.S. Navy SEAL who served as the United States Secretary of the Interior under President Donald Trump.
  • E. Kim Reynolds
    Kim Reynolds is an American Republican politician serving as the governor of Iowa and known for her conservative policies on taxes, education, and public health.
  • 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_69c008fb879c81909f5bfa56fadc1d46 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01fdec3588190b0af7d2ca8e8ee9b completed March 22, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c02826d84c8190a745e891ac2cccb8 completed March 22, 2026, 5:34 p.m.
Created at: March 22, 2026, 3:35 p.m.