Triple

T12608447

Position	Surface form	Disambiguated ID	Type / Status
Subject	褒章	`E301046`	entity
Predicate	hasType	`P0`	FINISHED
Object	紫綬褒章紫綬褒章は、日本政府が学術、芸術、スポーツなどの分野で優れた業績を挙げた個人に授与する名誉ある褒章の一つです。	`E995891`	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: 紫綬褒章 | Statement: [褒章, hasType, 紫綬褒章]

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

Target entity: 紫綬褒章
Context triple: [褒章, hasType, 紫綬褒章]

A. 紅綬褒章
紅綬褒章は、日本において公共の利益のために多額の私財を寄付した個人などに授与される名誉ある褒章の一つです。
B. 緑綬褒章
緑綬褒章は、日本政府が長年にわたるボランティア活動や社会奉仕に尽力した個人に授与する褒章の一つです。
C. 桐花大綬章
桐花大綬章 is one of Japan’s highest state decorations, awarded for exceptionally distinguished achievements in public service and other fields.
D. 功一級金鵄勲章
功一級金鵄勲章は、かつて日本において軍事上の卓越した功績を挙げた者に授与された最高位クラスの金鵄勲章である。
E. 勲一等瑞宝章
勲一等瑞宝章は、日本政府が長年にわたる公共への功労者に授与する高位の栄典勲章です。
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: 紫綬褒章
Triple: [褒章, hasType, 紫綬褒章]

Generated description

紫綬褒章は、日本政府が学術、芸術、スポーツなどの分野で優れた業績を挙げた個人に授与する名誉ある褒章の一つです。

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

Target entity: 紫綬褒章
Target entity description: 紫綬褒章は、日本政府が学術、芸術、スポーツなどの分野で優れた業績を挙げた個人に授与する名誉ある褒章の一つです。

A. 紅綬褒章
紅綬褒章は、日本において公共の利益のために多額の私財を寄付した個人などに授与される名誉ある褒章の一つです。
B. 緑綬褒章
緑綬褒章は、日本政府が長年にわたるボランティア活動や社会奉仕に尽力した個人に授与する褒章の一つです。
C. 桐花大綬章
桐花大綬章 is one of Japan’s highest state decorations, awarded for exceptionally distinguished achievements in public service and other fields.
D. 功一級金鵄勲章
功一級金鵄勲章は、かつて日本において軍事上の卓越した功績を挙げた者に授与された最高位クラスの金鵄勲章である。
E. 勲一等瑞宝章
勲一等瑞宝章は、日本政府が長年にわたる公共への功労者に授与する高位の栄典勲章です。
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_69d7bdea2ca881908f379526c13b1145`	completed	April 9, 2026, 2:55 p.m.
NER	Named-entity recognition	`batch_69d954e90efc81909951dbe698afa851`	completed	April 10, 2026, 7:52 p.m.
NED1	Entity disambiguation (via context triple)	`batch_69f6686b9d088190832d1f244e7aa924`	completed	May 2, 2026, 9:11 p.m.
NEDg	Description generation	`batch_69f66a602f088190984fa3381b5be944`	completed	May 2, 2026, 9:19 p.m.
NED2	Entity disambiguation (via description)	`batch_69f66b18e68881908bf79ab52bcc909e`	completed	May 2, 2026, 9:22 p.m.

Created at: April 9, 2026, 5:11 p.m.