Triple

T5520538
Position Surface form Disambiguated ID Type / Status
Subject Zhangjiakou E144793 entity
Predicate borderedBy P224 FINISHED
Object Chengde E145651 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: Chengde | Statement: [Zhangjiakou, borderedBy, Chengde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chengde
Context triple: [Zhangjiakou, borderedBy, Chengde]
  • A. Chengde chosen
    Chengde is a historic city in northeastern China best known for its Qing dynasty Mountain Resort, a vast imperial summer retreat and UNESCO World Heritage Site.
  • B. Baoding
    Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
  • C. Langfang
    Langfang is a prefecture-level city in northern China situated between Beijing and Tianjin, known for its strategic location and growing industrial and service sectors.
  • D. Zhangjiakou
    Zhangjiakou is a major city in northern China known as a key gateway between Beijing and Inner Mongolia and as one of the host locations for the 2022 Winter Olympics.
  • E. Pinghu City
    Pinghu City is a county-level coastal city in northern Zhejiang Province, China, known for its manufacturing industry and proximity to Shanghai across Hangzhou Bay.
  • 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_69c008f873a481909b4d9f7e2db3c37d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f7082ac8190a372fa75e8dec6a4 completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027e995e88190833762cb94a781cc completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:33 p.m.