Triple

T20174136
Position Surface form Disambiguated ID Type / Status
Subject GMA3: What You Need to Know E492043 entity
Predicate alsoKnownAs P39 FINISHED
Object GMA3: WYNK 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: GMA3: WYNK | Statement: [GMA3: What You Need to Know, alsoKnownAs, GMA3: WYNK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GMA3: WYNK
Context triple: [GMA3: What You Need to Know, alsoKnownAs, GMA3: WYNK]
  • A. GMA3: What You Need to Know chosen
    GMA3: What You Need to Know is an American daytime news and talk program that offers a mix of current events, human-interest stories, and lifestyle segments as part of the Good Morning America franchise.
  • B. 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.
  • C. GMA Day
    GMA Day was a daytime talk show spin-off of ABC’s Good Morning America that served as the predecessor to Strahan, Sara and Keke.
  • D. GMAZ
    GMAZ is the ICAO airport code for Zagora Airport in Morocco.
  • E. GMA Network Center
    GMA Network Center is the main headquarters and broadcast complex of GMA Network in Quezon City, Philippines, housing its television, radio, and film production operations.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6684a33688190b22cfc16907e76bc completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:36 p.m.