Triple

T10056939
Position Surface form Disambiguated ID Type / Status
Subject Tokyo National Museum E208886 entity
Predicate hasBuilding P105 FINISHED
Object Toyokan
Toyokan is a gallery building of the Tokyo National Museum that primarily showcases Asian art and archaeological artifacts from regions outside Japan.
 E952602 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: Toyokan | Statement: [Tokyo National Museum, hasBuilding, Toyokan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Toyokan
Context triple: [Tokyo National Museum, hasBuilding, Toyokan]
  • A. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • B. Daigo
    Daigo was the era name (nengō) in Japanese history corresponding to the reign of Emperor Daigo in the early 10th century.
  • C. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • D. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • E. Yokosuka
    Yokosuka is a coastal city in Kanagawa Prefecture, Japan, known for its major naval base and strategic location at the mouth of Tokyo Bay.
  • 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: Toyokan
Triple: [Tokyo National Museum, hasBuilding, Toyokan]
Generated description
Toyokan is a gallery building of the Tokyo National Museum that primarily showcases Asian art and archaeological artifacts from regions outside Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Toyokan
Target entity description: Toyokan is a gallery building of the Tokyo National Museum that primarily showcases Asian art and archaeological artifacts from regions outside Japan.
  • A. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • B. Daigo
    Daigo was the era name (nengō) in Japanese history corresponding to the reign of Emperor Daigo in the early 10th century.
  • C. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • D. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • E. Yokosuka
    Yokosuka is a coastal city in Kanagawa Prefecture, Japan, known for its major naval base and strategic location at the mouth of Tokyo Bay.
  • 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_69ca836094408190a36a1ea7e9a86fcd completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcfae503881909b9f016da4e2207d completed April 2, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f416ab88e48190b3089caab7987191 completed May 1, 2026, 2:57 a.m.
NEDg Description generation batch_69f41f16f43c81909f5d36e8b4b0b9c3 completed May 1, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f4225a4b5c8190958aaddbd10035b1 completed May 1, 2026, 3:47 a.m.
Created at: March 30, 2026, 8:57 p.m.