Triple

T5892302
Position Surface form Disambiguated ID Type / Status
Subject Ken Watanabe E131018 entity
Predicate familyName P18 FINISHED
Object Watanabe
Watanabe is a common Japanese surname borne by many notable figures in fields such as acting, sports, politics, and the arts.
 E552835 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: Watanabe | Statement: [Ken Watanabe, familyName, Watanabe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Watanabe
Context triple: [Ken Watanabe, familyName, Watanabe]
  • A. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • B. Hayashi
    Hayashi is a common Japanese surname that literally means "forest" and is equivalent to the Chinese surname "Lin."
  • C. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • D. Tanaka
    Tanaka is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and other fields.
  • E. Kiyokawa
    Kiyokawa is a small rural village in Kanagawa Prefecture, Japan, known for its mountainous scenery and outdoor recreation.
  • 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: Watanabe
Triple: [Ken Watanabe, familyName, Watanabe]
Generated description
Watanabe is a common Japanese surname borne by many notable figures in fields such as acting, sports, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Watanabe
Target entity description: Watanabe is a common Japanese surname borne by many notable figures in fields such as acting, sports, politics, and the arts.
  • A. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • B. Hayashi
    Hayashi is a common Japanese surname that literally means "forest" and is equivalent to the Chinese surname "Lin."
  • C. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • D. Tanaka
    Tanaka is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and other fields.
  • E. Kiyokawa
    Kiyokawa is a small rural village in Kanagawa Prefecture, Japan, known for its mountainous scenery and outdoor recreation.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036b45bec81908a13f39bbc181a59 completed March 22, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b14c2ff081908243988d5815be6d completed March 23, 2026, 3:19 a.m.
NEDg Description generation batch_69c0b1fabe448190be7d93b1f8c17c2a completed March 23, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69c0b29fbec8819092b117bd40e3731f completed March 23, 2026, 3:25 a.m.
Created at: March 22, 2026, 3:58 p.m.