Triple

T10468394
Position Surface form Disambiguated ID Type / Status
Subject Breaking and Entering E246861 entity
Predicate featuresCharacter P626 FINISHED
Object Liv E243189 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: Liv | Statement: [Breaking and Entering, featuresCharacter, Liv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liv
Context triple: [Breaking and Entering, featuresCharacter, Liv]
  • A. Liv chosen
    Liv is a feminine given name, often used in Scandinavian countries and popularized internationally by actress Liv Tyler.
  • B. Liv Lo
    Liv Lo is a Taiwanese television host, fitness entrepreneur, and yoga instructor known for her work in wellness and as the wife of actor Henry Golding.
  • C. Lou
    Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
  • D. Lou
    Lou is a recurring Springfield police officer on the animated television series "The Simpsons," known as Chief Wiggum’s level-headed, deadpan partner.
  • E. Lou
    Lou is a central character in the Canadian romantic drama film "Take This Waltz," which explores themes of love, fidelity, and emotional restlessness.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5092ef810819093a4d1df83aeac09 completed April 7, 2026, 1:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d89ff1cd948190a1ef331fb810bf26 completed April 10, 2026, 7 a.m.
Created at: April 6, 2026, 12:20 p.m.