Triple

T13257943
Position Surface form Disambiguated ID Type / Status
Subject Will Yun Lee E315710 entity
Predicate portrayed P1668 FINISHED
Object Harada
Harada is a fictional character from the X-Men film universe, depicted as a skilled Japanese warrior and bodyguard in "The Wolverine."
 E1275025 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: Harada | Statement: [Will Yun Lee, portrayed, Harada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harada
Context triple: [Will Yun Lee, portrayed, Harada]
  • A. Hadano
    Hadano is a city in Kanagawa Prefecture, Japan, known for its natural scenery, hiking trails, and proximity to the Tanzawa Mountains.
  • B. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • C. Munakata
    Munakata is a coastal city in Japan known for its ancient Munakata Taisha Shinto shrines and its location in northern Fukuoka Prefecture on Kyushu Island.
  • D. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • E. Hiranaka
    Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
  • 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: Harada
Triple: [Will Yun Lee, portrayed, Harada]
Generated description
Harada is a fictional character from the X-Men film universe, depicted as a skilled Japanese warrior and bodyguard in "The Wolverine."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harada
Target entity description: Harada is a fictional character from the X-Men film universe, depicted as a skilled Japanese warrior and bodyguard in "The Wolverine."
  • A. Hadano
    Hadano is a city in Kanagawa Prefecture, Japan, known for its natural scenery, hiking trails, and proximity to the Tanzawa Mountains.
  • B. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • C. Munakata
    Munakata is a coastal city in Japan known for its ancient Munakata Taisha Shinto shrines and its location in northern Fukuoka Prefecture on Kyushu Island.
  • D. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • E. Hiranaka
    Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f7614fc8190a1cac076d706e9aa completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01d27210b4819099aed53a2820591a completed May 11, 2026, 12:58 p.m.
NEDg Description generation batch_6a01d30961788190881f78d1989bd4ae completed May 11, 2026, 1 p.m.
NED2 Entity disambiguation (via description) batch_6a01d65ce2a48190a78e58b643de699a completed May 11, 2026, 1:15 p.m.
Created at: April 9, 2026, 9:25 p.m.