Triple

T10402485
Position Surface form Disambiguated ID Type / Status
Subject Marv Albert E245180 entity
Predicate employer P7 FINISHED
Object MSG Network E106046 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: MSG Network | Statement: [Marv Albert, employer, MSG Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MSG Network
Context triple: [Marv Albert, employer, MSG Network]
  • A. MSG Network chosen
    MSG Network is a regional sports television network based in New York, best known for broadcasting New York Knicks and Rangers games and related programming.
  • B. USA Network
    USA Network is an American basic cable television channel known for its original drama series, syndicated programming, and broad mainstream entertainment.
  • C. Nine Network
    Nine Network is a major Australian commercial television network known for broadcasting popular news, sports, and entertainment programming nationwide.
  • D. The Sports Network
    The Sports Network (TSN) is a Canadian English-language sports television network known for broadcasting major national and international sporting events, sports news, and analysis.
  • E. Mutual Sports Network
    Mutual Sports Network was the sports broadcasting division of the Mutual Broadcasting System, providing live coverage and commentary of major athletic events to its radio affiliates.
  • 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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9e42da08190a5383df3df6d3c18 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fbd13c888190b3a79a9aacb5291e completed April 9, 2026, 7:19 p.m.
Created at: April 6, 2026, 12:08 p.m.