Triple

T23408802
Position Surface form Disambiguated ID Type / Status
Subject Russian lease of Liaodong Peninsula E560008 entity
Predicate location P40 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: [Russian lease of Liaodong Peninsula, location, Dalian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dalian
Context triple: [Russian lease of Liaodong Peninsula, location, 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_69e2454b3a5881909c64773dc8a5d289 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a50fff10819094e71fb0c11b7d95 completed April 29, 2026, 6:28 a.m.
Created at: April 17, 2026, 5:38 p.m.