Triple

T8620807
Position Surface form Disambiguated ID Type / Status
Subject Peter Andrews E204157 entity
Predicate usedInFilm P795 FINISHED
Object Kimi E662973 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: Kimi | Statement: [Peter Andrews, usedInFilm, Kimi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimi
Context triple: [Peter Andrews, usedInFilm, Kimi]
  • A. Kimi chosen
    Kimi is a 2022 techno-thriller film starring Zoë Kravitz as an agoraphobic tech worker who uncovers evidence of a violent crime through a virtual assistant’s audio data.
  • B. Kima
    Kima is a small settlement located on Car Nicobar Island in the Nicobar district of India’s Andaman and Nicobar Islands.
  • C. Ukyo
    Ukyo is a Japanese given name commonly used for males and borne by various real and fictional characters.
  • D. Ōkimi
    Ōkimi was the title used for the supreme ruler of early Japan’s Yamato state, a precursor to the later Japanese emperor.
  • E. Kai
    Kai is the fictional half-Japanese, half-English outcast and skilled warrior portrayed by Keanu Reeves in the fantasy samurai film "47 Ronin."
  • 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_69ca832ceab8819096e4a9f546695079 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc47167b188190b5d9a113db9b9511 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbdd6aac819091f6dd12815c3d94 completed April 2, 2026, 6:56 p.m.
Created at: March 30, 2026, 6:26 p.m.