Triple

T14625409

Position	Surface form	Disambiguated ID	Type / Status
Subject	Fuchū	`E343330`	entity
Predicate	hasJapaneseName	`P9882`	FINISHED
Object	府中市府中市 is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the historic Ōkunitama Shrine.	`E1109896`	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: 府中市 | Statement: [Fuchū, hasJapaneseName, 府中市]

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07

Target entity: 府中市
Context triple: [Fuchū, hasJapaneseName, 府中市]

A. 御所市
御所市 is a small city in Nara Prefecture, Japan, known for its historical sites, traditional rural scenery, and proximity to the Kongo and Katsuragi mountain ranges.
B. 宇治市
宇治市は、京都府南部に位置し、世界遺産の平等院や宇治茶の産地として知られる歴史と文化の都市です。
C. 高槻市
高槻市は、大阪府北部に位置し、京都と大阪の中間にあるベッドタウン兼商工業都市です。
D. 国分寺市
国分寺市は、東京都多摩地域に位置し、歴史ある武蔵国分寺跡や緑豊かな住宅地として知られる市です。
E. 枚方市
枚方市は、大阪府北東部に位置し、淀川沿いに広がる住宅都市兼商業都市として発展している市です。
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: 府中市
Triple: [Fuchū, hasJapaneseName, 府中市]

Generated description

府中市 is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the historic Ōkunitama Shrine.

NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07

Target entity: 府中市
Target entity description: 府中市 is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the historic Ōkunitama Shrine.

A. 御所市
御所市 is a small city in Nara Prefecture, Japan, known for its historical sites, traditional rural scenery, and proximity to the Kongo and Katsuragi mountain ranges.
B. 宇治市
宇治市は、京都府南部に位置し、世界遺産の平等院や宇治茶の産地として知られる歴史と文化の都市です。
C. 高槻市
高槻市は、大阪府北部に位置し、京都と大阪の中間にあるベッドタウン兼商工業都市です。
D. 国分寺市
国分寺市は、東京都多摩地域に位置し、歴史ある武蔵国分寺跡や緑豊かな住宅地として知られる市です。
E. 枚方市
枚方市は、大阪府北東部に位置し、淀川沿いに広がる住宅都市兼商業都市として発展している市です。
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_69d822dffc3c8190aa173b90761bffda`	completed	April 9, 2026, 10:06 p.m.
NER	Named-entity recognition	`batch_69deb46a4a9081908472b0a542028a7f`	completed	April 14, 2026, 9:40 p.m.
NED1	Entity disambiguation (via context triple)	`batch_69fda92a6b9c8190bdb220444cfbe34a`	completed	May 8, 2026, 9:13 a.m.
NEDg	Description generation	`batch_69fdb1ad32a4819088e5831f3d74ea4e`	completed	May 8, 2026, 9:49 a.m.
NED2	Entity disambiguation (via description)	`batch_69fdb316479c81909343196bb89e5e57`	completed	May 8, 2026, 9:55 a.m.

Created at: April 10, 2026, 1:26 a.m.