Triple

T3485702
Position Surface form Disambiguated ID Type / Status
Subject Princess Mako E73601 entity
Predicate birthName P65 FINISHED
Object Mako
Mako is a Japanese imperial family member best known as Princess Mako of Akishino, the former princess who left royal status upon her marriage to a commoner.
E361169 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: Mako | Statement: [Princess Mako, birthName, Mako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mako
Context triple: [Princess Mako, birthName, Mako]
  • A. Mako
    Mako was a Japanese-American actor and voice actor known for his distinctive voice and roles in films like "Conan the Barbarian" and as the voice of Iroh in "Avatar: The Last Airbender."
  • B. Samu
    Samu is a given name, commonly used as a short form or variant of Samuel in various cultures.
  • C. Kai
    Kai is the fictional half-Japanese, half-English outcast and skilled warrior portrayed by Keanu Reeves in the fantasy samurai film "47 Ronin."
  • D. Kai
    Kai is the eldest granddaughter of former U.S. President Donald Trump and the daughter of Donald Trump Jr.
  • E. Taroa
    Taroa is the main settlement and administrative center of Maloelap Atoll in the Marshall Islands, known historically for its World War II-era Japanese airbase.
  • 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: Mako
Triple: [Princess Mako, birthName, Mako]
Generated description
Mako is a Japanese imperial family member best known as Princess Mako of Akishino, the former princess who left royal status upon her marriage to a commoner.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mako
Target entity description: Mako is a Japanese imperial family member best known as Princess Mako of Akishino, the former princess who left royal status upon her marriage to a commoner.
  • A. Mako
    Mako was a Japanese-American actor and voice actor known for his distinctive voice and roles in films like "Conan the Barbarian" and as the voice of Iroh in "Avatar: The Last Airbender."
  • B. Samu
    Samu is a given name, commonly used as a short form or variant of Samuel in various cultures.
  • C. Kai
    Kai is the fictional half-Japanese, half-English outcast and skilled warrior portrayed by Keanu Reeves in the fantasy samurai film "47 Ronin."
  • D. Kai
    Kai is the eldest granddaughter of former U.S. President Donald Trump and the daughter of Donald Trump Jr.
  • E. Taroa
    Taroa is the main settlement and administrative center of Maloelap Atoll in the Marshall Islands, known historically for its World War II-era Japanese airbase.
  • 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_69ad85cca8d4819088494e9f3340fab5 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbb8f205c8190aa6f7484ebad14bb completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b368248f9c81908a1905a705e57c53 completed March 13, 2026, 1:28 a.m.
NEDg Description generation batch_69b36a2231008190820b0c50ad2d661a completed March 13, 2026, 1:36 a.m.
NED2 Entity disambiguation (via description) batch_69b36a8dae1481908b10a966ebcf89b2 completed March 13, 2026, 1:38 a.m.
Created at: March 8, 2026, 3:18 p.m.