Triple

T12592538

Position	Surface form	Disambiguated ID	Type / Status
Subject	世田谷区	`E300641`	entity
Predicate	contains	`P35`	FINISHED
Object	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.	`E993875`	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: 玉川 | Statement: [世田谷区, contains, 玉川]

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

Target entity: 玉川
Context triple: [世田谷区, contains, 玉川]

A. 白川
白川 is a picturesque canal in Kyoto, Japan, renowned for its traditional townscape and cherry blossom-lined banks.
B. 桂川
桂川は、京都市内を流れ嵐山の景観で知られる日本の代表的な河川の一つです。
C. 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。
D. 庄川
庄川は日本の中部地方を流れ、富山県の庄川峡などの景勝地や水力発電で知られる河川である。
E. 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。
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: 玉川
Triple: [世田谷区, contains, 玉川]

Generated description

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.

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

Target entity: 玉川
Target entity description: 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.

A. 白川
白川 is a picturesque canal in Kyoto, Japan, renowned for its traditional townscape and cherry blossom-lined banks.
B. 桂川
桂川は、京都市内を流れ嵐山の景観で知られる日本の代表的な河川の一つです。
C. 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。
D. 庄川
庄川は日本の中部地方を流れ、富山県の庄川峡などの景勝地や水力発電で知られる河川である。
E. 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。
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_69d7bde87b648190bcd0266e9efde098`	completed	April 9, 2026, 2:55 p.m.
NER	Named-entity recognition	`batch_69d954cc6d3c81908fbb22601c46f3f7`	completed	April 10, 2026, 7:51 p.m.
NED1	Entity disambiguation (via context triple)	`batch_69f65ec2dac88190bf31bb00f93feb30`	completed	May 2, 2026, 8:29 p.m.
NEDg	Description generation	`batch_69f66308087c81908ab5b5795f255e37`	completed	May 2, 2026, 8:48 p.m.
NED2	Entity disambiguation (via description)	`batch_69f663fe2fac8190bb70c8f1b919d657`	completed	May 2, 2026, 8:52 p.m.

Created at: April 9, 2026, 5:07 p.m.