Triple

T18608046
Position Surface form Disambiguated ID Type / Status
Subject Chieko Wataya E454810 entity
Predicate givenName P17 FINISHED
Object Chieko
Chieko is a Japanese feminine given name commonly borne by women in various fields such as entertainment, arts, and literature.
 E1358972 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: Chieko | Statement: [Chieko Wataya, givenName, Chieko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Chieko
Context triple: [Chieko Wataya, givenName, Chieko]
  • A. Chikako
    Chikako is a Japanese feminine given name that can be written with various kanji characters and is borne by several notable women in Japan.
  • B. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • C. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • D. Yukiko
    Yukiko is a character in Haruki Murakami’s novel "South of the Border, West of the Sun," serving as a figure from the protagonist’s past whose reappearance profoundly affects his adult life and relationships.
  • E. Keiko
    Keiko was a famous captive orca best known for starring in the film "Free Willy" and later becoming the focus of a high-profile rehabilitation and release effort.
  • 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: Chieko
Triple: [Chieko Wataya, givenName, Chieko]
Generated description
Chieko is a Japanese feminine given name commonly borne by women in various fields such as entertainment, arts, and literature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Chieko
Target entity description: Chieko is a Japanese feminine given name commonly borne by women in various fields such as entertainment, arts, and literature.
  • A. Chikako
    Chikako is a Japanese feminine given name that can be written with various kanji characters and is borne by several notable women in Japan.
  • B. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • C. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • D. Yukiko
    Yukiko is a character in Haruki Murakami’s novel "South of the Border, West of the Sun," serving as a figure from the protagonist’s past whose reappearance profoundly affects his adult life and relationships.
  • E. Keiko
    Keiko was a famous captive orca best known for starring in the film "Free Willy" and later becoming the focus of a high-profile rehabilitation and release effort.
  • 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_69d8d38bbe7c8190bdec3138e7d413c9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54cff3be8819080ab20045bd18a4d completed April 19, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a05e655968c8190a414e54fe4ee21b7 completed May 14, 2026, 3:12 p.m.
NEDg Description generation batch_6a05e716f8c0819083745ef72848f99f completed May 14, 2026, 3:15 p.m.
NED2 Entity disambiguation (via description) batch_6a05e7791b0c81909921b2364915b733 completed May 14, 2026, 3:17 p.m.
Created at: April 10, 2026, 11:45 a.m.