Triple

T20363732
Position Surface form Disambiguated ID Type / Status
Subject Taoxian area of Shenyang E496852 entity
Predicate locatedIn P40 FINISHED
Object Shenyang 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: Shenyang | Statement: [Taoxian area of Shenyang, locatedIn, Shenyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shenyang
Context triple: [Taoxian area of Shenyang, locatedIn, Shenyang]
  • 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. 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.
  • 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. Anshan
    Anshan is a major industrial city in northeastern China, historically known as one of the country’s leading steel-producing centers.
  • 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.