Triple

T20166802
Position Surface form Disambiguated ID Type / Status
Subject Dan Pfeiffer E491842 entity
Predicate twitterUsername P2943 FINISHED
Object danpfeiffer NE NERFINISHED

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: danpfeiffer | Statement: [Dan Pfeiffer, twitterUsername, danpfeiffer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: danpfeiffer
Context triple: [Dan Pfeiffer, twitterUsername, danpfeiffer]
  • A. Dan Pfeiffer chosen
    Dan Pfeiffer is an American political strategist and former White House communications director who served as a senior adviser to President Barack Obama.
  • B. Dan
    Dan is the protagonist of Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," a post-scarcity future resident of a reputation-based society centered around a Disney theme park.
  • C. Dan
    Dan is a male given name commonly used in English-speaking countries, often as a short form of Daniel.
  • D. Dan
    Dan is a central character in Louisa May Alcott's novel "Jo's Boys," known for his rough past, adventurous spirit, and deep loyalty to the Bhaer family.
  • E. Dan
    Dan, better known as the Duke of Zhou, was an influential early Zhou dynasty statesman and regent in ancient China renowned for consolidating royal power and shaping foundational political and ritual institutions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66844e49081909b7e9ec2b65cc61d completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.