Triple

T17313480

Position	Surface form	Disambiguated ID	Type / Status
Subject	Ono	`E420360`	entity
Predicate	canBeWrittenAs	`P12679`	FINISHED
Object	大野大野 is a common Japanese surname and place name typically written with the kanji meaning “large field.”	`E1261972`	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: 大野 | Statement: [Ono, canBeWrittenAs, 大野]

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

Target entity: 大野
Context triple: [Ono, canBeWrittenAs, 大野]

A. 天野川
天野川は大阪府交野市を流れる、七夕伝説や星にまつわるロマンチックな物語で知られる川です。
B. 吉井川
吉井川は、岡山県などを流れて瀬戸内海に注ぐ、中国地方を代表する一級河川の一つです。
C. 大山巌
大山巌は、日清戦争・日露戦争で活躍し元帥陸軍大将となった、日本近代陸軍を代表する軍人・政治家である。
D. 玉川
玉川 is a district in Tokyo’s Setagaya Ward known for its riverside location along the Tama River and its mix of residential areas and commercial facilities.
E. 石川
石川は大阪府東部を流れ、大和川水系に属する中小河川です。
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: 大野
Triple: [Ono, canBeWrittenAs, 大野]

Generated description

大野 is a common Japanese surname and place name typically written with the kanji meaning “large field.”

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

Target entity: 大野
Target entity description: 大野 is a common Japanese surname and place name typically written with the kanji meaning “large field.”

A. 天野川
天野川は大阪府交野市を流れる、七夕伝説や星にまつわるロマンチックな物語で知られる川です。
B. 吉井川
吉井川は、岡山県などを流れて瀬戸内海に注ぐ、中国地方を代表する一級河川の一つです。
C. 大山巌
大山巌は、日清戦争・日露戦争で活躍し元帥陸軍大将となった、日本近代陸軍を代表する軍人・政治家である。
D. 玉川
玉川 is a district in Tokyo’s Setagaya Ward known for its riverside location along the Tama River and its mix of residential areas and commercial facilities.
E. 石川
石川は大阪府東部を流れ、大和川水系に属する中小河川です。
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_69d889d22b848190a4663d0b8f8f76e7`	completed	April 10, 2026, 5:25 a.m.
NER	Named-entity recognition	`batch_69e4399a4194819091d34cd3fffc8072`	completed	April 19, 2026, 2:10 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0180e6e830819097b33d6b99232727`	completed	May 11, 2026, 7:10 a.m.
NEDg	Description generation	`batch_6a01853590d081908f6523c55e4f610d`	completed	May 11, 2026, 7:28 a.m.
NED2	Entity disambiguation (via description)	`batch_6a01860e39788190bbf5ca5188352d95`	completed	May 11, 2026, 7:32 a.m.

Created at: April 10, 2026, 5:43 a.m.