Triple

T1691158
Position Surface form Disambiguated ID Type / Status
Subject Busan Station E36550 entity
Predicate near P350 FINISHED
Object Busan Port E4279 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: Busan Port | Statement: [Busan Station, near, Busan Port]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan Port
Context triple: [Busan Station, near, Busan Port]
  • A. Yantai Port
    Yantai Port is a major seaport city and shipping hub on the Bohai Sea coast in northeastern Shandong Province, China.
  • B. Busan chosen
    Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
  • C. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • D. Port of Dalian
    The Port of Dalian is a major deep-water seaport in northeastern China that serves as a key gateway for international trade and shipping in the Bohai Sea region.
  • E. Port of Kawasaki
    The Port of Kawasaki is a major industrial and commercial seaport in Kanagawa Prefecture, Japan, serving as a key logistics and manufacturing hub within the Greater Tokyo area.
  • 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6298fa748190acabb9f1d42bd3f5 completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad79947c908190b807205bd44c3254 completed March 8, 2026, 1:28 p.m.
Created at: March 4, 2026, 7:29 p.m.