Triple

T11117430
Position Surface form Disambiguated ID Type / Status
Subject The Burghers of Calais E262923 entity
Predicate hasCopy P16932 FINISHED
Object Seoul, South Korea E19209 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: Seoul, South Korea | Statement: [The Burghers of Calais, hasCopy, Seoul, South Korea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul, South Korea
Context triple: [The Burghers of Calais, hasCopy, Seoul, South Korea]
  • A. Inchon, South Korea
    Inchon, South Korea is a major port city near Seoul known for its strategic coastal location and as the site of the pivotal Korean War amphibious landing.
  • B. Suwon, South Korea
    Suwon, South Korea is a major city just south of Seoul known for its high-tech industry and the UNESCO-listed Hwaseong Fortress.
  • C. Jinju, South Korea
    Jinju, South Korea is a historic city in South Gyeongsang Province known for its riverside fortress, role in the Imjin War, and annual lantern festival.
  • D. Seoul chosen
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • E. Osan, South Korea
    Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a transportation and commercial hub south of Seoul.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79af638b08190b7ade5eb0cab6b75 completed April 9, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441cb16bc81908b5321506f655e38 completed April 19, 2026, 2:45 a.m.
Created at: April 8, 2026, 9:27 p.m.