Triple

T20363691
Position Surface form Disambiguated ID Type / Status
Subject Three Northeastern Provinces E496850 entity
Predicate hasMajorCity P316 FINISHED
Object Dalian 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: Dalian | Statement: [Three Northeastern Provinces, hasMajorCity, Dalian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dalian
Context triple: [Three Northeastern Provinces, hasMajorCity, Dalian]
  • A. Dalian chosen
    Dalian is a major port city in northeastern China known for its strategic location on the Liaodong Peninsula, maritime trade, and modern urban development.
  • B. Yingkou
    Yingkou is a coastal port city in northeastern China’s Liaoning Province, known as an important industrial and shipping hub on the Bohai Sea.
  • C. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • D. Panjin
    Panjin is an industrial and oil-producing city in northeastern China, best known for its striking Red Beach wetlands along the Bohai Sea.
  • E. Huludao
    Huludao is a coastal city in southwestern Liaoning Province, China, known for its port, shipbuilding industry, and seaside tourism.
  • 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_69e0b4a4f9b081908a5a021919c21ccb completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6786fd0088190908187ab642344cc completed April 20, 2026, 7:03 p.m.
Created at: April 16, 2026, 11:26 a.m.