Triple

T8363590
Position Surface form Disambiguated ID Type / Status
Subject KTX E197067 entity
Predicate primaryRoute P6298 FINISHED
Object Seoul–Busan E716382 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–Busan | Statement: [KTX, primaryRoute, Seoul–Busan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul–Busan
Context triple: [KTX, primaryRoute, Seoul–Busan]
  • A. Seoul–Busan chosen
    Seoul–Busan refers to the major intercity corridor in South Korea connecting the capital Seoul with the southeastern port city of Busan, one of the country’s busiest and most important travel routes.
  • B. Seoul–Jinju
    Seoul–Jinju is a major intercity rail corridor in South Korea connecting the capital, Seoul, with the southern city of Jinju.
  • C. Busan–Ulsan section
    The Busan–Ulsan section is a coastal railway segment in southeastern South Korea that connects the major port city of Busan with the industrial city of Ulsan.
  • D. Busan Metro
    Busan Metro is the rapid transit system serving the city of Busan, South Korea, providing extensive urban and suburban rail transportation across the metropolitan area.
  • E. Daegu
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • 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_69ca82f2dbe48190aba982e75a0d94de completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80768b208190a5f6c9e6cb6e7f30 completed March 31, 2026, 8:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce6ccf66d48190a457e0ea869b278e completed April 2, 2026, 1:19 p.m.
Created at: March 30, 2026, 6 p.m.