Triple

T11473698
Position Surface form Disambiguated ID Type / Status
Subject Travel Channel E271971 entity
Predicate subjectOf P38 FINISHED
Object Travel Channel (U.S. TV network) E271971 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: Travel Channel (U.S. TV network) | Statement: [Travel Channel, subjectOf, Travel Channel (U.S. TV network)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Travel Channel (U.S. TV network)
Context triple: [Travel Channel, subjectOf, Travel Channel (U.S. TV network)]
  • A. Travel Channel chosen
    Travel Channel is an American cable television network focused on travel, adventure, and exploration-themed programming around the world.
  • B. Sky Channel
    Sky Channel was the original name of Sky One, a British satellite television channel known for airing a mix of entertainment, drama, and imported US programming.
  • C. Super Channel
    Super Channel is a Canadian premium television network known for broadcasting a mix of original series, films, and international programming.
  • D. TNT network
    TNT network is an American cable television channel known for airing drama series, sports coverage, and feature films.
  • E. Channel 5
    Channel 5 is a British free-to-air television network known for a mix of entertainment, documentaries, and imported programming.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294b3f388190a587c358313f7260 completed April 9, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e95a479c81909a330c9721bd3902 completed April 20, 2026, 8:52 a.m.
Created at: April 8, 2026, 9:35 p.m.