Triple

T18761409
Position Surface form Disambiguated ID Type / Status
Subject Magnet TV E458775 entity
Predicate title P38 FINISHED
Object Magnet TV 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: Magnet TV | Statement: [Magnet TV, title, Magnet TV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magnet TV
Context triple: [Magnet TV, title, Magnet TV]
  • A. Magnet TV chosen
    Magnet TV is a pioneering 1965 video art piece by Nam June Paik that uses a magnet to distort a live television image, challenging conventional notions of broadcast media and visual perception.
  • B. Magnetes
    Magnetes were an ancient Greek tribe from the region of Magnesia in Thessaly, known from myth and history as participants in wider Hellenic religious and political affairs.
  • C. The Magnet
    The Magnet is a 1950 British comedy film, often noted for its whimsical portrayal of childhood and moral dilemmas, directed by Charles Frend.
  • D. Maa TV
    Maa TV is an Indian Telugu-language television channel known for its popular entertainment programming, including serials, reality shows, and films.
  • E. Antenna TV
    Antenna TV is an American digital multicast television network that primarily airs classic television series from the 1950s through the early 2000s.
  • 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_69d8d395dba0819087568404508590cb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e58d7fd5008190823bc7e37fdd6669 completed April 20, 2026, 2:20 a.m.
Created at: April 10, 2026, 11:52 a.m.