Triple

T8113974

Position	Surface form	Disambiguated ID	Type / Status
Subject	Sasebo	`E189425`	entity
Predicate	hasJapaneseName	`P9882`	FINISHED
Object	佐世保市佐世保市は、長崎県北部に位置し、米海軍基地やハウステンボスなどで知られる港湾工業都市です。	`E713166`	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: 佐世保市 | Statement: [Sasebo, hasJapaneseName, 佐世保市]

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

Target entity: 佐世保市
Context triple: [Sasebo, hasJapaneseName, 佐世保市]

A. 豊後大野市
豊後大野市は、大分県南部に位置し、豊かな自然景観や農業を特色とする市です。
B. 熊本市
熊本市 is the capital and largest city of Kumamoto Prefecture on Japan’s Kyushu island, known for its historic Kumamoto Castle and rich samurai-era heritage.
C. 木津川市
木津川市は、京都府南部に位置し、奈良県に隣接する住宅都市・歴史観光地として発展している市です。
D. 江田島市
江田島市 is a coastal city in Hiroshima Prefecture, Japan, encompassing several islands in the Seto Inland Sea and known for its maritime scenery and naval academy.
E. 宍粟市
宍粟市は、兵庫県西部の中国山地に位置し、豊かな森林資源と自然環境を特徴とする市です。
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: 佐世保市
Triple: [Sasebo, hasJapaneseName, 佐世保市]

Generated description

佐世保市は、長崎県北部に位置し、米海軍基地やハウステンボスなどで知られる港湾工業都市です。

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

Target entity: 佐世保市
Target entity description: 佐世保市は、長崎県北部に位置し、米海軍基地やハウステンボスなどで知られる港湾工業都市です。

A. 豊後大野市
豊後大野市は、大分県南部に位置し、豊かな自然景観や農業を特色とする市です。
B. 熊本市
熊本市 is the capital and largest city of Kumamoto Prefecture on Japan’s Kyushu island, known for its historic Kumamoto Castle and rich samurai-era heritage.
C. 木津川市
木津川市は、京都府南部に位置し、奈良県に隣接する住宅都市・歴史観光地として発展している市です。
D. 江田島市
江田島市 is a coastal city in Hiroshima Prefecture, Japan, encompassing several islands in the Seto Inland Sea and known for its maritime scenery and naval academy.
E. 宍粟市
宍粟市は、兵庫県西部の中国山地に位置し、豊かな森林資源と自然環境を特徴とする市です。
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_69ca82baad008190ab2859712b9b1607`	completed	March 30, 2026, 2:03 p.m.
NER	Named-entity recognition	`batch_69cb432f2a24819097be6ab9b03567bd`	completed	March 31, 2026, 3:44 a.m.
NED1	Entity disambiguation (via context triple)	`batch_69cc943bdaa48190971bf57ae4fb5c21`	completed	April 1, 2026, 3:42 a.m.
NEDg	Description generation	`batch_69cc95586fc08190b16a1b0798ef6e31`	completed	April 1, 2026, 3:47 a.m.
NED2	Entity disambiguation (via description)	`batch_69cc96533cb88190b9c1fda1fc969cad`	completed	April 1, 2026, 3:51 a.m.

Created at: March 30, 2026, 5:32 p.m.