Triple

T5718269
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Metropolitan Government Building E126073 entity
Predicate hasNickname P39 FINISHED
Object Tocho
Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
 E542719 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: Tocho | Statement: [Tokyo Metropolitan Government Building, hasNickname, Tocho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tocho
Context triple: [Tokyo Metropolitan Government Building, hasNickname, Tocho]
  • A. Takaro
    Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
  • B. Chimariko
    Chimariko is an extinct Native American language once spoken by the Chimariko people in northwestern California.
  • C. Ōtoku
    Ōtoku was a Japanese era name (nengō) of the late 11th century, used during the reign of Emperor Shirakawa.
  • D. Hacha-Kekan
    Hacha-Kekan is a traditional cultural festival of the Karbi people that showcases their indigenous rituals, music, dance, and communal celebrations.
  • E. Asago
    Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
  • 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: Tocho
Triple: [Tokyo Metropolitan Government Building, hasNickname, Tocho]
Generated description
Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tocho
Target entity description: Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
  • A. Takaro
    Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
  • B. Chimariko
    Chimariko is an extinct Native American language once spoken by the Chimariko people in northwestern California.
  • C. Ōtoku
    Ōtoku was a Japanese era name (nengō) of the late 11th century, used during the reign of Emperor Shirakawa.
  • D. Hacha-Kekan
    Hacha-Kekan is a traditional cultural festival of the Karbi people that showcases their indigenous rituals, music, dance, and communal celebrations.
  • E. Asago
    Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
  • 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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024e084cc81909a652f7c10d32c32 completed March 22, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07df49eb881908189fc8afb2ed478 completed March 22, 2026, 11:40 p.m.
NEDg Description generation batch_69c0877e28fc8190b12029b86bebe608 completed March 23, 2026, 12:21 a.m.
NED2 Entity disambiguation (via description) batch_69c087dbef588190949666371984c97f completed March 23, 2026, 12:22 a.m.
Created at: March 22, 2026, 3:46 p.m.