Triple

T20476895
Position Surface form Disambiguated ID Type / Status
Subject Ungjin E502339 entity
Predicate locatedInPresentDay P40 FINISHED
Object Gongju 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: Gongju | Statement: [Ungjin, locatedInPresentDay, Gongju]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gongju
Context triple: [Ungjin, locatedInPresentDay, Gongju]
  • A. Gongju chosen
    Gongju is a historic city in South Korea that once served as the capital of the ancient Baekje Kingdom and is renowned for its rich archaeological heritage.
  • B. Yeongju
    Yeongju is a city in eastern South Korea known for its historic temples, Confucian academies, and scenic mountainous landscapes.
  • C. Gyeongju
    Gyeongju is a historic city in South Korea famed for its rich cultural heritage and numerous archaeological sites from the ancient Silla Kingdom.
  • D. Gimhae
    Gimhae is a city in South Gyeongsang Province, South Korea, known for its historical significance as the birthplace of the ancient Gaya confederacy and its proximity to the metropolitan city of Busan.
  • E. Gwangmyeong
    Gwangmyeong is a city in South Korea known for its proximity to Seoul and attractions like the Gwangmyeong Cave, a former mine turned cultural and tourism complex.
  • 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_69e0b4af32848190aea80682b44d5d6e completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6996584648190a1a6dfcb57782b7f completed April 20, 2026, 9:23 p.m.
Created at: April 16, 2026, 11:34 a.m.