Triple

T3530441
Position Surface form Disambiguated ID Type / Status
Subject Shinagawa E74645 entity
Predicate hasSisterCity P919 FINISHED
Object Shenyang, China 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: Shenyang, China | Statement: [Shinagawa, hasSisterCity, Shenyang, China]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shenyang, China
Context triple: [Shinagawa, hasSisterCity, Shenyang, China]
  • A. Shenyang chosen
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • B. 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.
  • C. 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.
  • D. Anshan
    Anshan is a major industrial city in northeastern China, historically known as one of the country’s leading steel-producing centers.
  • E. Anshan
    Anshan was an ancient city and region in southwestern Iran that served as an early center of Elamite and later Achaemenid Persian power.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9764a881908aa8d25dc9adf59e completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e97536881908d5ed3dfe602c9e0 completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.