Triple

T2938459
Position Surface form Disambiguated ID Type / Status
Subject Chinese Northeastern Army E79326 entity
Predicate garrison P75 FINISHED
Object Mukden E20553 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: Mukden | Statement: [Chinese Northeastern Army, garrison, Mukden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mukden
Context triple: [Chinese Northeastern Army, garrison, Mukden]
  • A. Shenyang chosen
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • B. Dalian
    Dalian is a major port city in northeastern China known for its strategic location on the Liaodong Peninsula, maritime trade, and modern urban development.
  • C. Dandong
    Dandong is a northeastern Chinese border city on the Yalu River, known as a key gateway for trade and transport between China and North Korea.
  • D. Changchun
    Changchun is a major city in northeastern China that served as the capital of the Japanese puppet state of Manchukuo during the early 20th century.
  • E. Harbin
    Harbin is a major city in northeastern China known for its Russian-influenced architecture and its internationally famous annual ice and snow festival.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad986c1c0c8190a6a9f17082438cfd completed March 8, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108d4e5408190a0dd3728c5cf6a47 completed March 11, 2026, 6:16 a.m.
Created at: March 8, 2026, 2:56 p.m.