Triple

T3939166
Position Surface form Disambiguated ID Type / Status
Subject 2020 New Hampshire gubernatorial election E91989 entity
Predicate losingCandidate P354 FINISHED
Object Dan Feltes E399943 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: Dan Feltes | Statement: [2020 New Hampshire gubernatorial election, losingCandidate, Dan Feltes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Feltes
Context triple: [2020 New Hampshire gubernatorial election, losingCandidate, Dan Feltes]
  • A. Dan Feltes chosen
    Dan Feltes is an American lawyer and Democratic politician who served in the New Hampshire State Senate and ran for governor of New Hampshire in 2020.
  • B. Robert Hohman
    Robert Hohman is an American entrepreneur best known as the co-founder and former CEO of Glassdoor, a popular platform for anonymous employee reviews and salary information.
  • C. Dan Foos
    Dan Foos is a writer best known as the creator of the story for the film "Red Eye."
  • D. Bill Elfers
    Bill Elfers was an American venture capitalist best known for co-founding the influential Silicon Valley and Boston-based firm Greylock Partners.
  • E. Fred Schuler
    Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
  • 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_69aed965502c8190904ebad1203a4ae8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedfb12b88190a6ca6574b1aadb6e completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b556173f848190bf8b879a7c61a43f completed March 14, 2026, 12:35 p.m.
Created at: March 9, 2026, 3:24 p.m.