Triple

T9769484
Position Surface form Disambiguated ID Type / Status
Subject Manchukuo Imperial Army E237083 entity
Predicate garrison P75 FINISHED
Object Changchun E164950 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: Changchun | Statement: [Manchukuo Imperial Army, garrison, Changchun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changchun
Context triple: [Manchukuo Imperial Army, garrison, Changchun]
  • A. Changchun chosen
    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.
  • B. Jilin City
    Jilin City is a major industrial and transportation hub in northeastern China, situated along the Songhua River in central Jilin Province.
  • C. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • D. Liaoyuan
    Liaoyuan is a prefecture-level city in northeastern China known for its coal mining history and location in the central part of Jilin Province.
  • 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_69ca84d831b8819090322686b47887ce completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda0f0c64c81908f3435dd49c0218b completed April 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bd05f2588190ab413d26342aa70f completed April 5, 2026, 1:38 a.m.
Created at: March 30, 2026, 8:26 p.m.