Triple

T2232639
Position Surface form Disambiguated ID Type / Status
Subject George Lopez E49202 entity
Predicate networkOfShow P833 FINISHED
Object TV Land E184625 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: TV Land | Statement: [George Lopez, networkOfShow, TV Land]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TV Land
Context triple: [George Lopez, networkOfShow, TV Land]
  • A. TV Land chosen
    TV Land is an American cable television network known for airing classic television series and original sitcoms aimed primarily at adult audiences.
  • B. TV One
    TV One is an American cable television network that primarily targets African American audiences with a mix of original series, movies, and lifestyle programming.
  • C. Freeform (TV channel)
    Freeform is an American cable television channel owned by Disney that primarily targets young adults with a mix of original series, movies, and acquired programming.
  • D. WGN America
    WGN America is a U.S.-based cable television network known for airing syndicated series, movies, and original programming to a national audience.
  • E. Nickelodeon
    Nickelodeon is a major American children’s television network and brand known for its animated series, live-action shows, and kids’ entertainment franchises.
  • 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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc06d26bc8190a85ddb6312d2df08 completed March 7, 2026, 6:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b001ee481909b28aea25ad7b906 completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:47 p.m.