Triple

T12946230
Position Surface form Disambiguated ID Type / Status
Subject Zoe Barnes E309772 entity
Predicate investigates P1857 FINISHED
Object Peter Russo E499318 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: Peter Russo | Statement: [Zoe Barnes, investigates, Peter Russo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Russo
Context triple: [Zoe Barnes, investigates, Peter Russo]
  • A. Peter Russo chosen
    Peter Russo is a troubled Pennsylvania congressman and key character in the political drama series "House of Cards."
  • B. Christopher Russo
    Christopher Russo is an American sports radio and television personality best known for his energetic, outspoken style on baseball and talk shows.
  • C. Pietro Russell
    Pietro Russell is the central character in Sebastian Faulks’s novel "A Fool’s Alphabet," whose life story is told through episodic, alphabetically ordered chapters spanning different times and places.
  • D. Jeff Russo
    Jeff Russo is an American composer and musician best known for his atmospheric scores for film, television, and video games, including series like Fargo and Star Trek: Discovery.
  • E. Peter Chase
    Peter Chase is a composer known for creating the musical score for the film "L'Appartement."
  • 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_69d7bdfb57a88190836b743e2825feca completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e1b3694819098527dcea3cfed93 completed April 10, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af75bc04819098d98c47fca48ac9 completed May 3, 2026, 2:14 a.m.
Created at: April 9, 2026, 5:43 p.m.