Triple

T1033701
Position Surface form Disambiguated ID Type / Status
Subject Manchuria E22309 entity
Predicate hasMajorCity P316 FINISHED
Object Shenyang 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 | Statement: [Manchuria, hasMajorCity, Shenyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shenyang
Context triple: [Manchuria, hasMajorCity, Shenyang]
  • 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. Anshan
    Anshan was an ancient city and region in southwestern Iran that served as an early center of Elamite and later Achaemenid Persian power.
  • D. 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.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b812c9948190a37c2b1d3d32ea38 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad4001bcd4819088f59e31e3ed79cf completed March 8, 2026, 9:23 a.m.
Created at: March 1, 2026, 7:41 p.m.