Triple

T1592242
Position Surface form Disambiguated ID Type / Status
Subject Sumida E34202 entity
Predicate borders P224 FINISHED
Object Kōtō
Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
E333569 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: Kōtō | Statement: [Sumida, borders, Kōtō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kōtō
Context triple: [Sumida, borders, Kōtō]
  • A. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • B. Musashino
    Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
  • C. Moriguchi
    Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
  • D. Suginami
    Suginami is a residential ward in western Tokyo, Japan, known for its quiet neighborhoods, anime studios, and vibrant local shopping streets.
  • 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: Kōtō
Triple: [Sumida, borders, Kōtō]
Generated description
Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kōtō
Target entity description: Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • A. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • B. Musashino
    Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
  • C. Moriguchi
    Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
  • D. Suginami
    Suginami is a residential ward in western Tokyo, Japan, known for its quiet neighborhoods, anime studios, and vibrant local shopping streets.
  • 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_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_69b235106b1c8190ae6d4d02aefd69a9 completed March 12, 2026, 3:37 a.m.
NEDg Description generation batch_69b23634df448190b63f08b107511cb2 completed March 12, 2026, 3:42 a.m.
NED2 Entity disambiguation (via description) batch_69b236f6ca1c8190ad3ca4f329d1a5ae completed March 12, 2026, 3:45 a.m.
Created at: March 4, 2026, 7:27 p.m.