Triple

T3408131
Position Surface form Disambiguated ID Type / Status
Subject Liaoning E71823 entity
Predicate historicalName P65 FINISHED
Object Fengtian E115788 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: Fengtian | Statement: [Liaoning, historicalName, Fengtian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fengtian
Context triple: [Liaoning, historicalName, Fengtian]
  • A. Fengtian chosen
    Fengtian is the historical name of Shenyang, a major city in northeastern China that has long served as a political and economic center of the region.
  • B. Lüshun
    Lüshun is a strategically important port city in northeastern China, historically known as Port Arthur and noted for its role in several major conflicts.
  • C. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • D. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • E. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9056acc8190a9c50ec374851ac8 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bdaf06c8190a8102a4e3c728066 completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:15 p.m.