Triple

T20257781
Position Surface form Disambiguated ID Type / Status
Subject Sabi E498749 entity
Predicate locatedInPresentDay P40 FINISHED
Object Buyeo-gun NE NERFINISHED

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: Buyeo-gun | Statement: [Sabi, locatedInPresentDay, Buyeo-gun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buyeo-gun
Context triple: [Sabi, locatedInPresentDay, Buyeo-gun]
  • A. Buyeo chosen
    Buyeo was an ancient Korean kingdom that emerged in northern Manchuria and northern Korea, playing a key role in the early formation of Korean states and culture.
  • B. Taebong
    Taebong was a short-lived Korean kingdom of the early 10th century that emerged during the Later Three Kingdoms period before being absorbed by Goryeo.
  • C. Tancheon
    Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
  • D. Hanseong
    Hanseong was the historical name for Seoul when it served as the capital of the Joseon Dynasty in Korea.
  • E. Kyongsong
    Kyongsong is a coastal town and county-level city in northeastern North Korea known for its hot springs and location along the Sea of Japan (East Sea).
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e674c7296c819092860942de8f28d5 completed April 20, 2026, 6:47 p.m.
Created at: April 11, 2026, 11:41 p.m.