Triple

T29043772
Position Surface form Disambiguated ID Type / Status
Subject 창원시 E738074 entity
Predicate hasTransportation P105 FINISHED
Object 창원역
창원역은 경상남도 창원시에 위치한 주요 철도역으로, 경전선과 KTX 등 열차가 정차하는 지역 교통의 중심지이다.
E1872800 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: 창원역 | Statement: [창원시, hasTransportation, 창원역]
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: 창원역
Triple: [창원시, hasTransportation, 창원역]
Generated description
창원역은 경상남도 창원시에 위치한 주요 철도역으로, 경전선과 KTX 등 열차가 정차하는 지역 교통의 중심지이다.

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_69f077efb3848190b41574e1670f6ae2 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f6605fcf7c8190b387ad7b65c9f025 completed May 2, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260bfbd67c8190944af3cc0eb77d6a completed June 8, 2026, 12:25 a.m.
NEDg Description generation batch_6a26103b50948190a67b288cf9f474ce completed June 8, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a261bab40048190b31f5b12454bedbf completed June 8, 2026, 1:32 a.m.
Created at: April 28, 2026, 10:03 a.m.