Triple

T22741599
Position Surface form Disambiguated ID Type / Status
Subject Dunhua E562427 entity
Predicate borderingAdministrativeUnit P224 FINISHED
Object Hunchun NE NERFINISHED

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: Hunchun | Statement: [Dunhua, borderingAdministrativeUnit, Hunchun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hunchun
Context triple: [Dunhua, borderingAdministrativeUnit, Hunchun]
  • A. Hunchun chosen
    Hunchun is a border city in northeastern China’s Jilin Province, known for its strategic location near the junction of China, Russia, and North Korea and its role in regional trade and development.
  • B. Baishan
    Baishan is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, forest resources, and proximity to Changbai Mountain.
  • C. Yanji
    Yanji is a city in northeastern China’s Jilin Province, known as a cultural and economic center of the ethnic Korean community near the North Korean border.
  • D. Hegang
    Hegang is a coal-mining city in northeastern Heilongjiang Province, China, located near the Russian border along the Amur River region.
  • E. Shuangyashan
    Shuangyashan is a coal-mining and industrial city in northeastern China known for its energy resources and heavy industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1797400fc8190bec26726f434f787 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:23 p.m.