Triple

T2492293
Position Surface form Disambiguated ID Type / Status
Subject Peril E52070 entity
Predicate author P4 FINISHED
Object Robert Costa E273433 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: Robert Costa | Statement: [Peril, author, Robert Costa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Costa
Context triple: [Peril, author, Robert Costa]
  • A. Robert Costa chosen
    Robert Costa is an American political journalist and author known for his in-depth reporting on U.S. politics and coauthoring high-profile books on the Trump era.
  • B. Paulo Costanzo
    Paulo Costanzo is a Canadian actor best known for his roles in films like "Road Trip" and TV series such as "Royal Pains" and "Joey."
  • C. Peter Scolari
    Peter Scolari was an American actor best known for his comedic and character roles on television series such as "Bosom Buddies" and "Newhart."
  • D. Carlos Lemos
    Carlos Lemos was a Brazilian architect known for his work on prominent modernist projects such as São Paulo’s iconic Copan Building.
  • E. Christian Gómez
    Christian Gómez is an Argentine attacking midfielder best known in the United States for his standout play with D.C. United in Major League Soccer.
  • 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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1914ca48190ab0a6cc5f1bd2f56 completed March 7, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b8429388190a2d1b1610511ea75 completed March 9, 2026, 8:20 p.m.
Created at: March 6, 2026, 9:45 p.m.