Triple

T16457422
Position Surface form Disambiguated ID Type / Status
Subject The Interview E399717 entity
Predicate character P662 FINISHED
Object Sook E203091 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: Sook | Statement: [The Interview, character, Sook]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sook
Context triple: [The Interview, character, Sook]
  • A. Sook chosen
    Sook is the elderly, eccentric, and deeply kind cousin who serves as the narrator’s beloved companion in Truman Capote’s autobiographical short story “A Christmas Memory.”
  • B. Suki
    Suki is a feminine given name, often used in English-speaking contexts and associated with figures in entertainment and popular culture.
  • C. Soo
    Soo is a Chinese-American surname notably borne by actress Phillipa Soo, known for originating the role of Eliza Hamilton in the Broadway musical "Hamilton."
  • D. Sojin
    Sojin is a given name, often used in East Asian cultures, that can refer to various individuals in entertainment, arts, and other fields.
  • E. Shōkū
    Shōkū was a prominent Japanese Buddhist monk of the Kamakura period and a leading disciple of Hōnen who helped develop and spread Pure Land (Jōdo) teachings.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d7dfd188190b03e9b4151a4d3d8 completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f51d93081909ede0adcf8e604d4 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.