Triple

T6877
Position Surface form Disambiguated ID Type / Status
Subject Tennessee Valley Authority E136 entity
Predicate shortName P43 FINISHED
Object TVA E136 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: TVA | Statement: [Tennessee Valley Authority, shortName, TVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TVA
Context triple: [Tennessee Valley Authority, shortName, TVA]
  • A. Tennessee Valley Authority chosen
    The Tennessee Valley Authority is a federally owned U.S. corporation created during the New Deal to provide regional economic development, flood control, and electricity generation in the Tennessee Valley.
  • B. Douglas
    Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
  • C. de Forest
    de Forest is a surname most notably associated with Lee de Forest, an American inventor and early pioneer of radio and electronic communication.
  • D. U.S. Nuclear Regulatory Commission
    The U.S. Nuclear Regulatory Commission is the federal agency responsible for overseeing and ensuring the safe use of nuclear materials and facilities in the United States.
  • E. Rogers
    Rogers is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
  • 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_69a23bb612708190b09f25385e4b63d1 completed Feb. 28, 2026, 12:49 a.m.
NER Named-entity recognition batch_69a23ff1903c8190a7d1051b4795eecd completed Feb. 28, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69a248d5b92481909a846984a8639067 completed Feb. 28, 2026, 1:45 a.m.
Created at: Feb. 28, 2026, 12:54 a.m.