Triple

T25895699
Position Surface form Disambiguated ID Type / Status
Subject 양산시 E652463 entity
Predicate adjacentTo P224 FINISHED
Object 김해시
김해시는 대한민국 경상남도에 위치한 도시로, 부산광역시와 인접해 있으며 김해국제공항과 가야 문화 유적으로 잘 알려져 있다.
E1765533 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: 김해시 | Statement: [양산시, adjacentTo, 김해시]
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: 김해시
Triple: [양산시, adjacentTo, 김해시]
Generated description
김해시는 대한민국 경상남도에 위치한 도시로, 부산광역시와 인접해 있으며 김해국제공항과 가야 문화 유적으로 잘 알려져 있다.

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_69e7ab3c6cc081908de59bfcc28ec19d completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6038411088190975af82ad1156963 completed May 2, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129c791bc88190ad59b6f207d37633 completed May 24, 2026, 6:36 a.m.
NEDg Description generation batch_6a129cdeb5a48190a9d63b019074e2de completed May 24, 2026, 6:38 a.m.
NED2 Entity disambiguation (via description) batch_6a129d64f3dc81909fe9ccc1db2ddaa1 completed May 24, 2026, 6:40 a.m.
Created at: April 22, 2026, 8:23 a.m.