Triple

T498610
Position Surface form Disambiguated ID Type / Status
Subject North China E10349 entity
Predicate politicalCenter P4751 FINISHED
Object Beijing E2312 NE FINISHED

How this triple was built (3 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: Beijing | Statement: [North China, politicalCenter, Beijing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beijing
Context triple: [North China, politicalCenter, Beijing]
  • A. Beijing chosen
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • B. Shanghai
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • C. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • D. Wuhan
    Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
  • E. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: politicalCenter
Context triple: [North China, politicalCenter, Beijing]
  • A. traditionalPoliticalAlignment
    Indicates how closely an entity’s political views or affiliations align with established, historically dominant, or customary political positions within a given context.
  • B. politicalSpectrumPosition
    Indicates the relative ideological placement of an entity along a political spectrum (e.g., left–right, liberal–conservative).
  • C. politicalPattern
    Indicates a recurring or characteristic way in which political behaviors, decisions, or power dynamics are organized or expressed.
  • D. centralIn chosen
    Indicates that one entity occupies a central or most important position within another entity, context, or structure.
  • E. hasPopulationCenterType
    Indicates the classification of a population center by its type, such as city, town, village, or other settlement category.
  • F. None of above.

Provenance (4 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1183e988190bce70932a9678134 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5914232c481909a39cd3373e3c6c9 completed March 2, 2026, 1:31 p.m.
PD Predicate disambiguation batch_69a2edfa87cc8190a77c726a5a55b7d9 completed Feb. 28, 2026, 1:30 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.