Triple

T20332971
Position Surface form Disambiguated ID Type / Status
Subject ANO TV-Novosti E492529 entity
Predicate notableChannel P45103 FINISHED
Object RT en Español 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: RT en Español | Statement: [ANO TV-Novosti, notableChannel, RT en Español]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RT en Español
Context triple: [ANO TV-Novosti, notableChannel, RT en Español]
  • A. RT en Español chosen
    RT en Español is the Spanish-language international news channel of the Russian state-funded network RT, offering news and commentary tailored to Spanish-speaking audiences worldwide.
  • B. RTVE
    RTVE (Radiotelevisión Española) is Spain’s national public broadcasting corporation, operating multiple television, radio, and online services.
  • C. ES.TV
    ES.TV is an entertainment-focused television network and media brand known for celebrity interviews, movie-related content, and pop culture programming.
  • D. REN TV
    REN TV is a Russian television network known for its nationwide broadcasting of entertainment, news, and documentary programming.
  • E. CNN en Español
    CNN en Español is a Spanish-language news television channel providing 24-hour news coverage and analysis for audiences across Latin America, the United States, and other Spanish-speaking markets.
  • 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_69e0b4a1a09881908d97270d6971a25a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e677e886a08190952b828fedd2a411 completed April 20, 2026, 7 p.m.
Created at: April 16, 2026, 11:22 a.m.