Triple

T14531553
Position Surface form Disambiguated ID Type / Status
Subject Terrence Jenkins E340925 entity
Predicate notableWork P4 FINISHED
Object The Perfect Match E328568 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: The Perfect Match | Statement: [Terrence Jenkins, notableWork, The Perfect Match]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Perfect Match
Context triple: [Terrence Jenkins, notableWork, The Perfect Match]
  • A. The Perfect Match chosen
    The Perfect Match is a romantic comedy film produced by Flavor Unit Entertainment that follows a commitment-phobic bachelor whose views on love are challenged by an unexpected relationship.
  • B. A Perfect Match
    "A Perfect Match" is a pop song by Swedish teen pop group A-Teens, known for its catchy melody and upbeat, dance-oriented production.
  • C. The Love Match
    The Love Match is a British stage comedy (later adapted for film and television) best known for featuring actress Thora Hird in a prominent role.
  • D. The MatchMaker
    The MatchMaker is a romantic comedy film best known for its lighthearted story about love and relationships, released in the late 1990s.
  • E. A Match to the Heart
    "A Match to the Heart" is a reflective nonfiction book by Gretel Ehrlich that explores her near-fatal lightning strike and its profound impact on her understanding of nature, mortality, and the human spirit.
  • 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dea052d01c81909c8592c351be6f35 completed April 14, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a56872c8190a6d2421cb81aeeb1 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:22 a.m.