Triple

T25305050
Position Surface form Disambiguated ID Type / Status
Subject KR-48 E634457 entity
Predicate includesCounty P5971 FINISHED
Object Gimhae County
Gimhae County is a county-level administrative region in South Korea’s South Gyeongsang Province, known for its historical significance as the birthplace of the ancient Gaya confederacy.
E1793055 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: Gimhae County | Statement: [KR-48, includesCounty, Gimhae County]
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: Gimhae County
Triple: [KR-48, includesCounty, Gimhae County]
Generated description
Gimhae County is a county-level administrative region in South Korea’s South Gyeongsang Province, known for its historical significance as the birthplace of the ancient Gaya confederacy.

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_69e75a972c6481909bc11710e8d30a6c completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f49399bf3881908b36a2b009be4f87 completed May 1, 2026, 11:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a13031af8c48190a46f24c02e47ac13 completed May 24, 2026, 1:54 p.m.
NEDg Description generation batch_6a13046b77f08190be1b607b8fe3f277 completed May 24, 2026, 2 p.m.
NED2 Entity disambiguation (via description) batch_6a1304efd82481909d557a7c07c29c9f completed May 24, 2026, 2:02 p.m.
Created at: April 21, 2026, 1:25 p.m.