Triple

T9909057
Position Surface form Disambiguated ID Type / Status
Subject Bunkyo, Tokyo E185091 entity
Predicate hasOfficialName P66 FINISHED
Object Bunkyō-ku
Bunkyō-ku is a central Tokyo ward known for its universities, cultural institutions, and quiet residential neighborhoods.
 E918765 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-ku | Statement: [Bunkyo, Tokyo, hasOfficialName, Bunkyō-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bunkyō-ku
Context triple: [Bunkyo, Tokyo, hasOfficialName, Bunkyō-ku]
  • A. Chūō-ku
    Chūō-ku is a central ward of Osaka, Japan, known as a major commercial and entertainment hub featuring famous landmarks, shopping streets, and nightlife areas.
  • B. Chūō-ku
    Chūō-ku is a central ward of Fukuoka City in Japan, known as a major commercial, entertainment, and administrative hub.
  • C. Chūō-ku
    Chūō-ku is a central ward of Tokyo, Japan, known as a major commercial and business district that includes areas like Ginza and Nihonbashi.
  • D. Sumiyoshi-ku
    Sumiyoshi-ku is one of the 24 wards of Osaka, Japan, known as a primarily residential area with a mix of traditional neighborhoods and urban amenities.
  • E. Higashi-ku
    Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
  • 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-ku
Triple: [Bunkyo, Tokyo, hasOfficialName, Bunkyō-ku]
Generated description
Bunkyō-ku is a central Tokyo ward known for its universities, cultural institutions, and quiet residential neighborhoods.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bunkyō-ku
Target entity description: Bunkyō-ku is a central Tokyo ward known for its universities, cultural institutions, and quiet residential neighborhoods.
  • A. Chūō-ku
    Chūō-ku is a central ward of Osaka, Japan, known as a major commercial and entertainment hub featuring famous landmarks, shopping streets, and nightlife areas.
  • B. Chūō-ku
    Chūō-ku is a central ward of Fukuoka City in Japan, known as a major commercial, entertainment, and administrative hub.
  • C. Chūō-ku
    Chūō-ku is a central ward of Tokyo, Japan, known as a major commercial and business district that includes areas like Ginza and Nihonbashi.
  • D. Sumiyoshi-ku
    Sumiyoshi-ku is one of the 24 wards of Osaka, Japan, known as a primarily residential area with a mix of traditional neighborhoods and urban amenities.
  • E. Higashi-ku
    Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb50feb008190aa9c084f590c0ebd completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69e525100e108190b4f6949695c7156e completed April 19, 2026, 6:55 p.m.
NEDg Description generation batch_69e52a78951c8190923711067cf4e7e5 completed April 19, 2026, 7:18 p.m.
NED2 Entity disambiguation (via description) batch_69e5319b6ef0819096debabfb6ffbe70 completed April 19, 2026, 7:48 p.m.
Created at: March 30, 2026, 8:41 p.m.