Triple

T22166135
Position Surface form Disambiguated ID Type / Status
Subject Galavisión E547792 entity
Predicate sisterChannel P5818 FINISHED
Object TUDN USA 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: TUDN USA | Statement: [Galavisión, sisterChannel, TUDN USA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TUDN USA
Context triple: [Galavisión, sisterChannel, TUDN USA]
  • A. TUDN chosen
    TUDN is a Spanish-language sports television network and media brand focused on soccer and other sports, primarily serving audiences in the United States and Mexico.
  • B. TMDU
    TMDU is the commonly used abbreviation for Tokyo Medical and Dental University, a leading Japanese national university specializing in medical and dental education and research.
  • C. TNU
    TNU is the commonly used abbreviation for Tajik National University, a major public higher education institution in Tajikistan.
  • D. TUDa
    TUDa is a leading German research university located in Darmstadt, renowned for its engineering, computer science, and natural sciences programs.
  • E. UTDC
    UTDC (Urban Transportation Development Corporation) was a Canadian government-owned transit equipment manufacturer known for producing rail vehicles and other urban transportation systems before its assets were acquired by Bombardier.
  • 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_69e11e3c4c5c81908d336165816b12e0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12a314cc081908857c13d018d52b2 completed April 28, 2026, 9:44 p.m.
Created at: April 16, 2026, 8:34 p.m.