Triple

T4105774
Position Surface form Disambiguated ID Type / Status
Subject Matsuo Bashō E88446 entity
Predicate residence P75 FINISHED
Object Fukagawa
Fukagawa is a historic district in Tokyo, Japan, known for its old merchant quarters, temples, and its association with the haiku poet Matsuo Bashō.
 E525532 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: Fukagawa | Statement: [Matsuo Bashō, residence, Fukagawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fukagawa
Context triple: [Matsuo Bashō, residence, Fukagawa]
  • A. Fujikawa
    Fujikawa is a Japanese surname borne by various notable individuals, including professional baseball pitcher Kyuji Fujikawa.
  • B. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • C. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • D. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • E. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • 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: Fukagawa
Triple: [Matsuo Bashō, residence, Fukagawa]
Generated description
Fukagawa is a historic district in Tokyo, Japan, known for its old merchant quarters, temples, and its association with the haiku poet Matsuo Bashō.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fukagawa
Target entity description: Fukagawa is a historic district in Tokyo, Japan, known for its old merchant quarters, temples, and its association with the haiku poet Matsuo Bashō.
  • A. Fujikawa
    Fujikawa is a Japanese surname borne by various notable individuals, including professional baseball pitcher Kyuji Fujikawa.
  • B. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • C. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • D. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • E. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • 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_69aed9484fb881909146f4c772ad277c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af019af25481909e9f1d171356f3e8 completed March 9, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf91db342c819084d3f59157518128 completed March 22, 2026, 6:53 a.m.
NEDg Description generation batch_69bf9244e538819086f1ecc818e0d5cd completed March 22, 2026, 6:55 a.m.
NED2 Entity disambiguation (via description) batch_69bf92b95f248190b7260625ce1d18a2 completed March 22, 2026, 6:56 a.m.
Created at: March 9, 2026, 3:40 p.m.