Triple

T1592345
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Station E34204 entity
Predicate hasPart P35 FINISHED
Object Yaesu side building
Yaesu side building is a modern commercial and transportation complex on the Yaesu side of Tokyo Station, featuring offices, shops, and direct access to rail services.
 E181392 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: Yaesu side building | Statement: [Tokyo Station, hasPart, Yaesu side building]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yaesu side building
Context triple: [Tokyo Station, hasPart, Yaesu side building]
  • A. Kenwood
    Kenwood is a small community in California’s Sonoma Valley known for its wineries, vineyards, and scenic rural charm.
  • B. Mogami
    Mogami was a lead ship of a class of Japanese World War II heavy cruisers known for their high speed, heavy armament, and participation in major Pacific naval battles.
  • C. Hensoldt
    Hensoldt is a German defense and security electronics company specializing in advanced sensor solutions such as radars, optronics, and electronic warfare systems.
  • D. Yuasa
    Yuasa is a historic coastal town in Japan renowned as the birthplace of traditional soy sauce production.
  • E. Yoshimura
    Yoshimura is a Japanese surname borne by various notable individuals across fields such as politics, sports, and the arts.
  • 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: Yaesu side building
Triple: [Tokyo Station, hasPart, Yaesu side building]
Generated description
Yaesu side building is a modern commercial and transportation complex on the Yaesu side of Tokyo Station, featuring offices, shops, and direct access to rail services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yaesu side building
Target entity description: Yaesu side building is a modern commercial and transportation complex on the Yaesu side of Tokyo Station, featuring offices, shops, and direct access to rail services.
  • A. Kenwood
    Kenwood is a small community in California’s Sonoma Valley known for its wineries, vineyards, and scenic rural charm.
  • B. Mogami
    Mogami was a lead ship of a class of Japanese World War II heavy cruisers known for their high speed, heavy armament, and participation in major Pacific naval battles.
  • C. Hensoldt
    Hensoldt is a German defense and security electronics company specializing in advanced sensor solutions such as radars, optronics, and electronic warfare systems.
  • D. Yuasa
    Yuasa is a historic coastal town in Japan renowned as the birthplace of traditional soy sauce production.
  • E. Yoshimura
    Yoshimura is a Japanese surname borne by various notable individuals across fields such as politics, sports, and the arts.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb2c480008190bb472cfdab74c387 completed March 7, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad46a357d48190aa4151967ce6a947 completed March 8, 2026, 9:51 a.m.
NEDg Description generation batch_69ad4941fcb08190adfba998bdadd3ef completed March 8, 2026, 10:02 a.m.
NED2 Entity disambiguation (via description) batch_69ad4a05981881908a16c126254c2050 completed March 8, 2026, 10:05 a.m.
Created at: March 4, 2026, 7:27 p.m.