Triple

T36629551

Position	Surface form	Disambiguated ID	Type / Status
Subject	E8	`E904273`	entity
Predicate	connectsToExpressway	`P845`	FINISHED
Object	Nōetsu Expressway Nōetsu Expressway is a regional expressway in Japan that serves as a key coastal route along the Sea of Japan, linking communities and other major highways in the area.	`E2284827`	NE FINISHED

How this triple was built (2 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: Nōetsu Expressway | Statement: [E8, connectsToExpressway, Nōetsu Expressway]

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: Nōetsu Expressway
Triple: [E8, connectsToExpressway, Nōetsu Expressway]

Generated description

Nōetsu Expressway is a regional expressway in Japan that serves as a key coastal route along the Sea of Japan, linking communities and other major highways in the area.

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_69f76e6ae750819096911e6e2d4d12c5`	completed	May 3, 2026, 3:48 p.m.
NER	Named-entity recognition	`batch_69f7c4b31220819090fb90896185ce24`	completed	May 3, 2026, 9:57 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a44a358447c81908baf52ba9c329f15`	completed	July 1, 2026, 5:19 a.m.
NEDg	Description generation	`batch_6a44a4259a588190ac5e415d6796c8f0`	completed	July 1, 2026, 5:22 a.m.
NED2	Entity disambiguation (via description)	`batch_6a44a59a4e7081909521e8a5af0f7e13`	completed	July 1, 2026, 5:28 a.m.

Created at: May 3, 2026, 4:11 p.m.