Triple

T6688071
Position Surface form Disambiguated ID Type / Status
Subject Daejeon Station E152149 entity
Predicate connectsToCity P4245 FINISHED
Object Mokpo E613689 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: Mokpo | Statement: [Daejeon Station, connectsToCity, Mokpo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mokpo
Context triple: [Daejeon Station, connectsToCity, Mokpo]
  • A. Mokpo chosen
    Mokpo is a coastal city in South Jeolla Province, South Korea, known as a regional transportation hub and gateway to numerous nearby islands.
  • B. Gunsan
    Gunsan is a coastal city in North Jeolla Province, South Korea, known for its port, industrial facilities, and longstanding association with nearby military air operations.
  • C. Mokneung
    Mokneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
  • D. Suncheon
    Suncheon is a city in South Jeolla Province, South Korea, known for its ecological attractions such as the Suncheon Bay Wetland Reserve and its role as a regional administrative and cultural center.
  • E. Jinju-si
    Jinju-si is a city in South Gyeongsang Province, South Korea, known for its historic Jinju Fortress and the annual Namgang Yudeung (Lantern) Festival.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14feb28819097bc157df8a2f96e completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f7df860819099d50871dbe08ad9 completed March 28, 2026, 1:31 a.m.
Created at: March 27, 2026, 2:04 p.m.