Triple

T2534602
Position Surface form Disambiguated ID Type / Status
Subject GMA Network E56238 entity
Predicate abbreviation P43 FINISHED
Object GMA E56238 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: GMA | Statement: [GMA Network, abbreviation, GMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GMA
Context triple: [GMA Network, abbreviation, GMA]
  • A. GMA Network chosen
    GMA Network is a major Philippine commercial television and radio broadcasting company known for its nationwide reach and popular entertainment and news programs.
  • B. BMG Philippines
    BMG Philippines was the Philippine branch of the global music company Bertelsmann Music Group, responsible for signing, producing, and distributing music by local and international artists in the Philippines.
  • C. MGA
    MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • D. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • E. GMA3 (formerly Strahan, Sara and Keke)
    GMA3 (formerly Strahan, Sara and Keke) is a daytime spin-off of ABC’s Good Morning America that blends news, lifestyle segments, and celebrity interviews in a more informal talk-show format.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd27c8650819080005869789b802c completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2bbc416c81908774782420b54664 completed March 9, 2026, 8:21 p.m.
Created at: March 6, 2026, 9:47 p.m.