Triple

T16078654
Position Surface form Disambiguated ID Type / Status
Subject Suidobashi area E390040 entity
Predicate adjacentArea P17964 FINISHED
Object Jimbocho
Jimbocho is a Tokyo neighborhood famed for its dense concentration of used bookstores, publishing houses, and student-friendly cafes.
E1192605 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: Jimbocho | Statement: [Suidobashi area, adjacentArea, Jimbocho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jimbocho
Context triple: [Suidobashi area, adjacentArea, Jimbocho]
  • A. Jimbo
    Jimbo is a character from the Australian short film "I Love Sarah Jane," which follows a group of kids navigating adolescence amid a zombie apocalypse.
  • B. Jimbo
    Jimbo is an American college football coach best known for leading Florida State University to a national championship and later coaching at Texas A&M.
  • C. Shimabukuro
    Shimabukuro is a Japanese surname most notably associated with virtuoso ukulele player Jake Shimabukuro.
  • D. Jino
    Jino are an officially recognized ethnic minority group in China, primarily living in Yunnan Province and known for their distinct language and traditional culture.
  • E. Toyako
    Toyako is a town in Hokkaido, Japan, known as a gateway to the scenic Lake Tōya area and nearby volcanic and hot spring attractions.
  • 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: Jimbocho
Triple: [Suidobashi area, adjacentArea, Jimbocho]
Generated description
Jimbocho is a Tokyo neighborhood famed for its dense concentration of used bookstores, publishing houses, and student-friendly cafes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jimbocho
Target entity description: Jimbocho is a Tokyo neighborhood famed for its dense concentration of used bookstores, publishing houses, and student-friendly cafes.
  • A. Jimbo
    Jimbo is a character from the Australian short film "I Love Sarah Jane," which follows a group of kids navigating adolescence amid a zombie apocalypse.
  • B. Jimbo
    Jimbo is an American college football coach best known for leading Florida State University to a national championship and later coaching at Texas A&M.
  • C. Shimabukuro
    Shimabukuro is a Japanese surname most notably associated with virtuoso ukulele player Jake Shimabukuro.
  • D. Jino
    Jino are an officially recognized ethnic minority group in China, primarily living in Yunnan Province and known for their distinct language and traditional culture.
  • E. Toyako
    Toyako is a town in Hokkaido, Japan, known as a gateway to the scenic Lake Tōya area and nearby volcanic and hot spring attractions.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183c401a881908fcb0b753d2dfc8a completed April 17, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe48907148190ab04520717141788 completed May 10, 2026, 1:51 a.m.
NEDg Description generation batch_69ffe67043588190864864d40956682b completed May 10, 2026, 1:59 a.m.
NED2 Entity disambiguation (via description) batch_69ffe6f510cc8190b6b8c46c0356d36a completed May 10, 2026, 2:01 a.m.
Created at: April 10, 2026, 4:57 a.m.