Triple

T21957462

Position	Surface form	Disambiguated ID	Type / Status
Subject	Nissaka-juku	`E542228`	entity
Predicate	nameWrittenInJapanese	`P28734`	FINISHED
Object	日坂宿日坂宿は、東海道五十三次のひとつとして栄えた、現在の静岡県掛川市付近に位置する旧宿場町です。	`E1511203`	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: 日坂宿 | Statement: [Nissaka-juku, nameWrittenInJapanese, 日坂宿]

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

Target entity: 日坂宿
Context triple: [Nissaka-juku, nameWrittenInJapanese, 日坂宿]

A. Tsumago-juku
Tsumago-juku is a beautifully preserved former post town on the historic Nakasendō route in Japan, known for its traditional wooden buildings and Edo-period atmosphere.
B. 高千穂町
高千穂町は、宮崎県北西部に位置し、神話の里として知られる峡谷や高千穂神社などの観光名所で有名な町です。
C. 村野駅
村野駅は、大阪府交野市に位置し、京阪電気鉄道交野線が乗り入れる地域の生活拠点となっている鉄道駅です。
D. 美瑛町
美瑛町 is a picturesque town in Hokkaido, Japan, famed for its rolling patchwork hills, flower fields, and scenic rural landscapes.
E. 西柏崎駅
西柏崎駅は、新潟県柏崎市に位置するJR東日本越後線の駅です。
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: 日坂宿
Triple: [Nissaka-juku, nameWrittenInJapanese, 日坂宿]

Generated description

日坂宿は、東海道五十三次のひとつとして栄えた、現在の静岡県掛川市付近に位置する旧宿場町です。

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

Target entity: 日坂宿
Target entity description: 日坂宿は、東海道五十三次のひとつとして栄えた、現在の静岡県掛川市付近に位置する旧宿場町です。

A. Tsumago-juku
Tsumago-juku is a beautifully preserved former post town on the historic Nakasendō route in Japan, known for its traditional wooden buildings and Edo-period atmosphere.
B. 高千穂町
高千穂町は、宮崎県北西部に位置し、神話の里として知られる峡谷や高千穂神社などの観光名所で有名な町です。
C. 村野駅
村野駅は、大阪府交野市に位置し、京阪電気鉄道交野線が乗り入れる地域の生活拠点となっている鉄道駅です。
D. 美瑛町
美瑛町 is a picturesque town in Hokkaido, Japan, famed for its rolling patchwork hills, flower fields, and scenic rural landscapes.
E. 西柏崎駅
西柏崎駅は、新潟県柏崎市に位置するJR東日本越後線の駅です。
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_69e0c47fab1081908dc74a6545dbb051`	completed	April 16, 2026, 11:14 a.m.
NER	Named-entity recognition	`batch_69f1244108948190a08e6966e55c4acd`	completed	April 28, 2026, 9:18 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0a67082ee08190a791c5307d25a1a2`	completed	May 18, 2026, 1:10 a.m.
NEDg	Description generation	`batch_6a0a67910f0081908d3d4771be0fb167`	completed	May 18, 2026, 1:12 a.m.
NED2	Entity disambiguation (via description)	`batch_6a0a68038d148190a9b2811f23fa802e`	completed	May 18, 2026, 1:14 a.m.

Created at: April 16, 2026, 7:59 p.m.