Triple

T2873646
Position Surface form Disambiguated ID Type / Status
Subject Shibuya City E56823 entity
Predicate contains P35 FINISHED
Object Omotesandō
Omotesandō is a fashionable, tree-lined avenue in Tokyo known for its high-end boutiques, modern architecture, and trendy cafés.
 E367745 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: Omotesandō | Statement: [Shibuya City, contains, Omotesandō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Omotesandō
Context triple: [Shibuya City, contains, Omotesandō]
  • A. Omotesando Hills
    Omotesando Hills is a high-end shopping and residential complex in Tokyo’s Omotesandō district, known for its sleek, minimalist architecture and integration into the tree-lined boulevard’s urban landscape.
  • B. Fushimi
    Fushimi is a historic district in Kyoto, Japan, known for its castle and its association with key events and figures of the late Sengoku period.
  • C. Akiruno
    Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
  • D. Ueno
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • E. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • 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: Omotesandō
Triple: [Shibuya City, contains, Omotesandō]
Generated description
Omotesandō is a fashionable, tree-lined avenue in Tokyo known for its high-end boutiques, modern architecture, and trendy cafés.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Omotesandō
Target entity description: Omotesandō is a fashionable, tree-lined avenue in Tokyo known for its high-end boutiques, modern architecture, and trendy cafés.
  • A. Omotesando Hills
    Omotesando Hills is a high-end shopping and residential complex in Tokyo’s Omotesandō district, known for its sleek, minimalist architecture and integration into the tree-lined boulevard’s urban landscape.
  • B. Fushimi
    Fushimi is a historic district in Kyoto, Japan, known for its castle and its association with key events and figures of the late Sengoku period.
  • C. Akiruno
    Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
  • D. Ueno
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • E. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • 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_69ab4a4ced288190ab6d3e062d10f7f6 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abe0032ddc8190bb4d15ec7e3c63e8 completed March 7, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69b38ba5bc088190bd656c2959cdfb6a completed March 13, 2026, 3:59 a.m.
NEDg Description generation batch_69b3acb9a94c81909f6d0a3f43dc43e9 completed March 13, 2026, 6:20 a.m.
NED2 Entity disambiguation (via description) batch_69b3ad2484288190ad5c603418e984fb completed March 13, 2026, 6:22 a.m.
Created at: March 6, 2026, 10:03 p.m.