Triple

T20084312
Position Surface form Disambiguated ID Type / Status
Subject Seamus Tierney E500084 entity
Predicate knownFor P22 FINISHED
Object Love, Antosha NE NERFINISHED

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: Love, Antosha | Statement: [Seamus Tierney, knownFor, Love, Antosha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Love, Antosha
Context triple: [Seamus Tierney, knownFor, Love, Antosha]
  • A. Love, Antosha chosen
    Love, Antosha is a 2019 documentary film that chronicles the life and career of actor Anton Yelchin through home videos, interviews, and personal writings.
  • B. Larina
    Larina is a Russian surname most notably borne by Anna Larina, the widow of Bolshevik leader Nikolai Bukharin.
  • C. My Friend Ivan Lapshin
    My Friend Ivan Lapshin is a 1984 Soviet drama film by director Aleksei German, acclaimed for its atmospheric black-and-white portrayal of life in a provincial town in the pre–World War II Stalinist era.
  • D. Yuriatin
    Yuriatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Yuri Zhivago’s life and relationships.
  • E. The Russian Bride
    "The Russian Bride" is a work associated with British actress and author Sheila Hancock, likely a novel or written piece reflecting her storytelling and dramatic sensibilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655a2d2c81908a6b8fd2f209a825 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.