Triple

T947085
Position Surface form Disambiguated ID Type / Status
Subject Manchukuo E20436 entity
Predicate capital P234 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, capital, Changchun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changchun
Context triple: [Manchukuo, capital, 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. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • C. Jinzhou
    Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
  • D. Anshan
    Anshan was an ancient city and region in southwestern Iran that served as an early center of Elamite and later Achaemenid Persian power.
  • E. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3be19448190a8863fce3d152430 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad293209648190a380175f85d6efcc completed March 8, 2026, 7:45 a.m.
Created at: March 1, 2026, 7:40 p.m.