Triple

T10846879
Position Surface form Disambiguated ID Type / Status
Subject 4*Town E256034 entity
Predicate hasMember P10 FINISHED
Object Tae Young
Tae Young is a member of the South Korean pop group 4*Town from the animated film "Turning Red."
 E889678 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: Tae Young | Statement: [4*Town, hasMember, Tae Young]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tae Young
Context triple: [4*Town, hasMember, Tae Young]
  • A. Lee Tae-hun
    Lee Tae-hun is a South Korean film producer known for his work on the international release of the science fiction thriller "Snowpiercer."
  • B. Yohan Lee
    Yohan Lee is a fictional character from the work "The Encyclopedists."
  • C. Peter Sohn
    Peter Sohn is an American animator, voice actor, and film director at Pixar known for his work on projects like "Ratatouille," "The Good Dinosaur," and "Elemental."
  • D. Ganke Lee
    Ganke Lee is Miles Morales’ best friend and tech-savvy confidant in Marvel’s Spider-Man stories, often supporting him with gadgets, strategy, and emotional grounding.
  • E. Ryu Jong-hyun
    Ryu Jong-hyun is a South Korean figure skating coach best known for having coached Olympic champion Yuna Kim earlier in her career.
  • 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: Tae Young
Triple: [4*Town, hasMember, Tae Young]
Generated description
Tae Young is a member of the South Korean pop group 4*Town from the animated film "Turning Red."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tae Young
Target entity description: Tae Young is a member of the South Korean pop group 4*Town from the animated film "Turning Red."
  • A. Lee Tae-hun
    Lee Tae-hun is a South Korean film producer known for his work on the international release of the science fiction thriller "Snowpiercer."
  • B. Yohan Lee
    Yohan Lee is a fictional character from the work "The Encyclopedists."
  • C. Peter Sohn
    Peter Sohn is an American animator, voice actor, and film director at Pixar known for his work on projects like "Ratatouille," "The Good Dinosaur," and "Elemental."
  • D. Ganke Lee
    Ganke Lee is Miles Morales’ best friend and tech-savvy confidant in Marvel’s Spider-Man stories, often supporting him with gadgets, strategy, and emotional grounding.
  • E. Ryu Jong-hyun
    Ryu Jong-hyun is a South Korean figure skating coach best known for having coached Olympic champion Yuna Kim earlier in her career.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75113bc188190ac78df0c51d95de6 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb162d718819081fbc3a082672b4f completed April 14, 2026, 9:28 p.m.
NEDg Description generation batch_69dec255abb08190bf93573c41aa35e9 completed April 14, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69dec7c48c3c81909365b901830f0906 completed April 14, 2026, 11:03 p.m.
Created at: April 8, 2026, 9:20 p.m.