Triple

T3364910
Position Surface form Disambiguated ID Type / Status
Subject Chiyoda E70810 entity
Predicate borders P224 FINISHED
Object Bunkyō
Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
 E469604 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: Bunkyō | Statement: [Chiyoda, borders, Bunkyō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bunkyō
Context triple: [Chiyoda, borders, Bunkyō]
  • 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. Kōtō
    Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • C. Chōfu
    Chōfu is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, film studios, and proximity to central Tokyo.
  • D. 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.
  • E. Yanaka
    Yanaka is a traditional, temple-filled neighborhood in Tokyo known for its preserved old-town atmosphere, narrow lanes, and historic cemetery.
  • 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: Bunkyō
Triple: [Chiyoda, borders, Bunkyō]
Generated description
Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bunkyō
Target entity description: Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
  • 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. Kōtō
    Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • C. Chōfu
    Chōfu is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, film studios, and proximity to central Tokyo.
  • D. 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.
  • E. Yanaka
    Yanaka is a traditional, temple-filled neighborhood in Tokyo known for its preserved old-town atmosphere, narrow lanes, and historic cemetery.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb28643f48190b78b0222f8323344 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69be43705d708190abea669829ef2970 completed March 21, 2026, 7:06 a.m.
NEDg Description generation batch_69be4544ebe88190a2391484ac3ab18d completed March 21, 2026, 7:14 a.m.
NED2 Entity disambiguation (via description) batch_69be45bc7b2c8190aa293d2c10077864 completed March 21, 2026, 7:16 a.m.
Created at: March 8, 2026, 3:13 p.m.