Triple

T10242863
Position Surface form Disambiguated ID Type / Status
Subject Suginami E243639 entity
Predicate contains P35 FINISHED
Object Ogikubo
Ogikubo is a residential and commercial district in western Tokyo known for its relaxed atmosphere, ramen shops, and role as a transport hub on the Chūō Line.
 E965190 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: Ogikubo | Statement: [Suginami, contains, Ogikubo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ogikubo
Context triple: [Suginami, contains, Ogikubo]
  • A. Ishkashimi
    Ishkashimi is a lesser-known Eastern Iranian language spoken by small communities in parts of Afghanistan and Tajikistan.
  • B. Shikaoi
    Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
  • C. Oyamazaki
    Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
  • D. Akiruno
    Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
  • E. Ikoma
    Ikoma is a city in Japan known for its scenic setting on the slopes of Mount Ikoma and its role as a residential and commuter hub near Osaka and Nara.
  • 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: Ogikubo
Triple: [Suginami, contains, Ogikubo]
Generated description
Ogikubo is a residential and commercial district in western Tokyo known for its relaxed atmosphere, ramen shops, and role as a transport hub on the Chūō Line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ogikubo
Target entity description: Ogikubo is a residential and commercial district in western Tokyo known for its relaxed atmosphere, ramen shops, and role as a transport hub on the Chūō Line.
  • A. Ishkashimi
    Ishkashimi is a lesser-known Eastern Iranian language spoken by small communities in parts of Afghanistan and Tajikistan.
  • B. Shikaoi
    Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
  • C. Oyamazaki
    Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
  • D. Akiruno
    Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
  • E. Ikoma
    Ikoma is a city in Japan known for its scenic setting on the slopes of Mount Ikoma and its role as a residential and commuter hub near Osaka and Nara.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d229c1ac8190a86e911aea47a56d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69f5f62d41448190ab65fb9c81d4d673 completed May 2, 2026, 1:03 p.m.
NEDg Description generation batch_69f600b51f488190a85a8f10f190b3c0 completed May 2, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_69f601ebaa448190ba59485d9d7d68d1 completed May 2, 2026, 1:53 p.m.
Created at: April 6, 2026, 11:25 a.m.