Triple

T12112005
Position Surface form Disambiguated ID Type / Status
Subject One PH E288454 entity
Predicate owner P347 FINISHED
Object TV5 Network E56496 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: TV5 Network | Statement: [One PH, owner, TV5 Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TV5 Network
Context triple: [One PH, owner, TV5 Network]
  • A. TV5 Network chosen
    TV5 Network is a major Philippine television and media company known for its free-to-air channel TV5 and various entertainment, news, and sports programming.
  • B. 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.
  • C. 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.
  • D. Maharlika Broadcasting System
    Maharlika Broadcasting System was the former name of the Philippine government-owned television network now known as PTV, which serves as the state’s primary public broadcasting service.
  • E. GMA News TV
    GMA News TV is a Philippine free-to-air television network known for its news, public affairs, and informational 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9156814148190b47d63a89fcab17c completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63ee285208190a0183e30c749f955 completed May 2, 2026, 6:13 p.m.
Created at: April 8, 2026, 9:49 p.m.