Triple

T8235729
Position Surface form Disambiguated ID Type / Status
Subject Busan Central Bus Terminal E192399 entity
Predicate connectsTo P845 FINISHED
Object Yangsan E159717 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: Yangsan | Statement: [Busan Central Bus Terminal, connectsTo, Yangsan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yangsan
Context triple: [Busan Central Bus Terminal, connectsTo, Yangsan]
  • A. Yangsan chosen
    Yangsan is a city in South Gyeongsang Province, South Korea, known as a growing residential and educational hub near Busan.
  • B. Jinyang
    Jinyang is the historical name of the city now known as Taiyuan, a major urban and industrial center in northern China’s Shanxi province.
  • C. Jinqiao
    Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
  • D. Songyuan
    Songyuan is a prefecture-level city in northwestern Jilin Province, China, known as an important regional hub for agriculture, petrochemicals, and transportation.
  • E. Xintai
    Xintai is a county-level city in Shandong Province, China, administered by the prefecture-level city of Tai'an.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb782a5e18819096235679f5a644a8 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd34fb069c8190965d69fae908482e completed April 1, 2026, 3:08 p.m.
Created at: March 30, 2026, 5:46 p.m.