Triple

T10296177
Position Surface form Disambiguated ID Type / Status
Subject Kaufman, Texas E241493 entity
Predicate namedAfter P63 FINISHED
Object David S. Kaufman E183747 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: David S. Kaufman | Statement: [Kaufman, Texas, namedAfter, David S. Kaufman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David S. Kaufman
Context triple: [Kaufman, Texas, namedAfter, David S. Kaufman]
  • A. David S. Kaufman chosen
    David S. Kaufman was a 19th-century Texas politician and statesman who served as a U.S. Congressman and played a significant role in the early political development of Texas.
  • B. Jeff Kodosky
    Jeff Kodosky is an American engineer and co-founder of National Instruments, best known as the "father of LabVIEW" for creating the influential graphical programming environment.
  • C. David Komansky
    David Komansky was an American businessman who served as chairman and CEO of Merrill Lynch, overseeing its expansion into a global financial services powerhouse in the 1990s and early 2000s.
  • D. Michael Resnick
    Michael Resnick is an American science fiction author and editor known for his prolific output and multiple Hugo Award–winning works.
  • E. Matt Kaufmann
    Matt Kaufmann is a computer scientist best known for his work on automated theorem proving and the ACL2 theorem prover, often in collaboration with J Strother Moore.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2ea9b3c8190b11518b259d5825c completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d75018383481909abbba8247a93f8e completed April 9, 2026, 7:07 a.m.
Created at: April 6, 2026, 11:43 a.m.