Triple

T20332970
Position Surface form Disambiguated ID Type / Status
Subject ANO TV-Novosti E492529 entity
Predicate notableChannel P45103 FINISHED
Object RT Arabic 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 Arabic | Statement: [ANO TV-Novosti, notableChannel, RT Arabic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RT Arabic
Context triple: [ANO TV-Novosti, notableChannel, RT Arabic]
  • A. RT Arabic chosen
    RT Arabic is the Arabic-language news and current affairs channel of the Russian state-funded international television network RT, targeting audiences in the Arab world and Arabic speakers globally.
  • B. Arabic
    Arabic is a Semitic language widely spoken across the Arab world and used as a liturgical language in Islam.
  • C. Razihi Arabic
    Razihi Arabic is a highly distinctive and conservative Arabic variety spoken in the Razih region of northwestern Yemen, noted for preserving archaic linguistic features.
  • D. Arabic Wikinews
    Arabic Wikinews is the Arabic-language edition of the Wikinews project, offering collaboratively written, free-content news articles for Arabic-speaking audiences.
  • E. Hijazi Arabic
    Hijazi Arabic is a major regional variety of Arabic spoken primarily in western Saudi Arabia, especially in the Hijaz region including cities like Mecca, Medina, and Jeddah.
  • 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.