Triple

T11634420
Position Surface form Disambiguated ID Type / Status
Subject GMA Pinoy TV E276478 entity
Predicate sisterChannel P5818 FINISHED
Object GMA Life TV E934718 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 Life TV | Statement: [GMA Pinoy TV, sisterChannel, GMA Life TV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GMA Life TV
Context triple: [GMA Pinoy TV, sisterChannel, GMA Life TV]
  • A. GMA Life TV chosen
    GMA Life TV is a Filipino pay television channel owned by GMA Network that features lifestyle, travel, food, and entertainment programming aimed primarily at overseas Filipino audiences.
  • B. GMA News TV
    GMA News TV is a Philippine free-to-air television network known for its news, public affairs, and informational programming.
  • C. GMA Network
    GMA Network is a major Philippine commercial television and radio broadcasting company known for its nationwide reach and popular entertainment and news programs.
  • D. GMA Pinoy TV
    GMA Pinoy TV is an international Filipino television channel that broadcasts GMA Network’s programs to audiences outside the Philippines.
  • E. Kapamilya Channel
    Kapamilya Channel is a Philippine pay television network that serves as a primary platform for ABS-CBN’s entertainment, news, and public affairs 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a25c0b00819095898d2b2445ecfb completed April 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87b12044819098a858edb2b16689 completed April 26, 2026, 9:46 p.m.
Created at: April 8, 2026, 9:39 p.m.