Triple

T32447695

Position	Surface form	Disambiguated ID	Type / Status
Subject	동구 (부산광역시)	`E829190`	entity
Predicate	hasHistoricArea	`P5057`	FINISHED
Object	초량 이바구길 일대 초량 이바구길 일대는 부산항과 원도심을 한눈에 내려다볼 수 있는 언덕길을 따라 근현대 도시 형성과 피란수도 시절의 흔적이 남아 있는 대표적인 역사·문화 관광지이다.	`E2007171`	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: 초량 이바구길 일대 | Statement: [동구 (부산광역시), hasHistoricArea, 초량 이바구길 일대]

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: 초량 이바구길 일대
Triple: [동구 (부산광역시), hasHistoricArea, 초량 이바구길 일대]

Generated description

초량 이바구길 일대는 부산항과 원도심을 한눈에 내려다볼 수 있는 언덕길을 따라 근현대 도시 형성과 피란수도 시절의 흔적이 남아 있는 대표적인 역사·문화 관광지이다.

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_69f3491d2e5c819092b1c9535beff8ec`	completed	April 30, 2026, 12:20 p.m.
NER	Named-entity recognition	`batch_69f6c2e767bc8190b49fd0c4a557b464`	completed	May 3, 2026, 3:37 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a346678b660819082bf871b00b4fb26`	completed	June 18, 2026, 9:43 p.m.
NEDg	Description generation	`batch_6a34674302f081908ce094e58ee8360c`	completed	June 18, 2026, 9:46 p.m.
NED2	Entity disambiguation (via description)	`batch_6a34682ebe448190b88c760af0af9dfa`	completed	June 18, 2026, 9:50 p.m.

Created at: May 1, 2026, 12:56 a.m.