Triple

T4035230
Position Surface form Disambiguated ID Type / Status
Subject Ex Machina E83811 entity
Predicate mainCharacter P1183 FINISHED
Object Kyoko
Kyoko is a mysterious, mostly silent android in the science fiction film "Ex Machina," serving as both assistant and unsettling presence within the reclusive inventor Nathan's isolated research facility.
 E407816 NE FINISHED

How this triple was built (4 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: Kyoko | Statement: [Ex Machina, mainCharacter, Kyoko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kyoko
Context triple: [Ex Machina, mainCharacter, Kyoko]
  • A. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • B. Naoko
    Naoko is a central, emotionally fragile character in Haruki Murakami’s story "Norwegian Wood," whose complex relationship with the protagonist explores themes of love, loss, and mental illness.
  • C. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • D. Atsuko
    Atsuko is a Japanese feminine given name commonly borne by women and princesses in Japan, with meanings that vary depending on the kanji used.
  • E. Masako
    Masako is the Empress of Japan, a former diplomat and Harvard-educated member of the Imperial House known for her international background and public role.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kyoko
Triple: [Ex Machina, mainCharacter, Kyoko]
Generated description
Kyoko is a mysterious, mostly silent android in the science fiction film "Ex Machina," serving as both assistant and unsettling presence within the reclusive inventor Nathan's isolated research facility.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kyoko
Target entity description: Kyoko is a mysterious, mostly silent android in the science fiction film "Ex Machina," serving as both assistant and unsettling presence within the reclusive inventor Nathan's isolated research facility.
  • A. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • B. Naoko
    Naoko is a central, emotionally fragile character in Haruki Murakami’s story "Norwegian Wood," whose complex relationship with the protagonist explores themes of love, loss, and mental illness.
  • C. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • D. Atsuko
    Atsuko is a Japanese feminine given name commonly borne by women and princesses in Japan, with meanings that vary depending on the kanji used.
  • E. Masako
    Masako is the Empress of Japan, a former diplomat and Harvard-educated member of the Imperial House known for her international background and public role.
  • F. None of above. chosen

Provenance (5 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb132f6c8190937acd35a6a5a9e4 completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b556415ebc8190a528c7e22dbf70df completed March 14, 2026, 12:36 p.m.
NEDg Description generation batch_69b556efc2148190a66e732e09e4fc21 completed March 14, 2026, 12:39 p.m.
NED2 Entity disambiguation (via description) batch_69b5575de0e88190843f1fcbc12c9dd5 completed March 14, 2026, 12:41 p.m.
Created at: March 9, 2026, 3:36 p.m.