Triple

T12958859
Position Surface form Disambiguated ID Type / Status
Subject Love, Victor E310084 entity
Predicate hasCharacter P2308 FINISHED
Object Andrew
Andrew is a recurring character in the teen drama series "Love, Victor," known as a popular yet initially antagonistic classmate who gradually reveals a more vulnerable and complex side.
E228 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: Andrew | Statement: [Love, Victor, hasCharacter, Andrew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andrew
Context triple: [Love, Victor, hasCharacter, Andrew]
  • A. John
    John is the birth name of American singer-songwriter and producer Teddy Geiger, known for writing and producing hits for artists like Shawn Mendes.
  • B. John
    John I, Count of Holland, was a medieval nobleman who ruled the County of Holland at the turn of the 14th century.
  • C. John
    John McDowell is a prominent South African-born philosopher known for his influential work in epistemology, philosophy of mind, and ethics.
  • D. John
    John Cicero was a late 15th-century Elector of Brandenburg from the House of Hohenzollern who helped consolidate the territory’s political and administrative structures within the Holy Roman Empire.
  • E. John
    John Brabourne was a British film and television producer and peer, known for producing works such as the 1979 adaptation of "Murder on the Orient Express."
  • 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: Andrew
Triple: [Love, Victor, hasCharacter, Andrew]
Generated description
Andrew is a recurring character in the teen drama series "Love, Victor," known as a popular yet initially antagonistic classmate who gradually reveals a more vulnerable and complex side.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Andrew
Target entity description: Andrew is a recurring character in the teen drama series "Love, Victor," known as a popular yet initially antagonistic classmate who gradually reveals a more vulnerable and complex side.
  • A. Andrew chosen
    Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
  • B. Andrew
    Andrew is a subway station in South Boston on the Massachusetts Bay Transportation Authority's Red Line.
  • C. John
    John is the birth name of American singer-songwriter and producer Teddy Geiger, known for writing and producing hits for artists like Shawn Mendes.
  • D. John
    John I, Count of Holland, was a medieval nobleman who ruled the County of Holland at the turn of the 14th century.
  • E. John
    John McDowell is a prominent South African-born philosopher known for his influential work in epistemology, philosophy of mind, and ethics.
  • F. None of above.

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_69d7bdfb57a88190836b743e2825feca completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e2e44908190bb8b43fc5c3b8a8a completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8dddd80819094c80ef405024419 completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6ba0904e8819098bae29961bf0046 completed May 3, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69f6bb7a0ae08190813411fa677430aa completed May 3, 2026, 3:05 a.m.
Created at: April 9, 2026, 5:44 p.m.