Triple

T6280020
Position Surface form Disambiguated ID Type / Status
Subject Talpa Media E140756 entity
Predicate notableWork P4 FINISHED
Object I Love My Country
I Love My Country is a television game show format created by Talpa Media in which celebrity teams compete in quizzes and challenges about their home nation.
 E583124 NE FINISHED

How this triple was built (4 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: I Love My Country | Statement: [Talpa Media, notableWork, I Love My Country]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: I Love My Country
Context triple: [Talpa Media, notableWork, I Love My Country]
  • A. To My Country
    "To My Country" is a patriotic poem by Indian writer Sarojini Naidu that expresses deep love and devotion to her homeland.
  • B. My Homeland
    "My Homeland" is the English title of "Mawtini," a famous patriotic anthem widely regarded as a symbol of national pride in the Arab world.
  • C. My Country
    "My Country" is the English title of "Negaraku," the national anthem of Malaysia.
  • D. My Country, My Country
    "My Country, My Country" is a 2006 documentary film by Laura Poitras that follows an Iraqi doctor and political candidate during the U.S. occupation and the country’s first post-invasion elections.
  • E. Our Fatherland
    "Our Fatherland" is the English title of "Mer Hayrenik," the national anthem of Armenia.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: I Love My Country
Triple: [Talpa Media, notableWork, I Love My Country]
Generated description
I Love My Country is a television game show format created by Talpa Media in which celebrity teams compete in quizzes and challenges about their home nation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: I Love My Country
Target entity description: I Love My Country is a television game show format created by Talpa Media in which celebrity teams compete in quizzes and challenges about their home nation.
  • A. To My Country
    "To My Country" is a patriotic poem by Indian writer Sarojini Naidu that expresses deep love and devotion to her homeland.
  • B. My Homeland
    "My Homeland" is the English title of "Mawtini," a famous patriotic anthem widely regarded as a symbol of national pride in the Arab world.
  • C. My Country
    "My Country" is the English title of "Negaraku," the national anthem of Malaysia.
  • D. My Country, My Country
    "My Country, My Country" is a 2006 documentary film by Laura Poitras that follows an Iraqi doctor and political candidate during the U.S. occupation and the country’s first post-invasion elections.
  • E. Our Fatherland
    "Our Fatherland" is the English title of "Mer Hayrenik," the national anthem of Armenia.
  • F. None of above. chosen

Provenance (5 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_69c008cc158881908df6ec94a911c736 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063ddb3a4819083455f6da854f8a9 completed March 22, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5195bcbb88190a8ff5958b5f89b4b completed March 26, 2026, 11:32 a.m.
NEDg Description generation batch_69c52cc711d48190bfcc6ab993b0eb31 completed March 26, 2026, 12:55 p.m.
NED2 Entity disambiguation (via description) batch_69c5931a61208190b7681d16c07ab90c completed March 26, 2026, 8:12 p.m.
Created at: March 22, 2026, 4:26 p.m.