Triple

T8627205
Position Surface form Disambiguated ID Type / Status
Subject Liaoshen Campaign E204307 entity
Predicate majorCityInvolved P38292 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: [Liaoshen Campaign, majorCityInvolved, Changchun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changchun
Context triple: [Liaoshen Campaign, majorCityInvolved, 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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5c2d852081908901f5d2a47035b0 completed March 31, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecc9abd1081909d45af7498ec7c34 completed April 2, 2026, 8:07 p.m.
Created at: March 30, 2026, 6:26 p.m.