Triple

T1695670
Position Surface form Disambiguated ID Type / Status
Subject Shaanxi Province E36651 entity
Predicate hasMajorCity P316 FINISHED
Object Baoji
Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
 E221560 NE FINISHED

How this triple was built (4 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: Baoji | Statement: [Shaanxi Province, hasMajorCity, Baoji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Baoji
Context triple: [Shaanxi Province, hasMajorCity, Baoji]
  • A. Bozhou
    Bozhou is a historic city in northern Anhui Province, China, known as a major center of traditional Chinese medicine and ancient culture.
  • B. Yan'an
    Yan'an is a historic city in China's Shaanxi province that served as the Chinese Communist Party's revolutionary base and political center during the late 1930s and 1940s.
  • C. Taian
    Taian is a prefecture-level city in eastern China's Shandong province, best known as the gateway to the sacred Mount Tai.
  • D. 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.
  • E. Xinjing
    Xinjing was the capital city of the Japanese puppet state of Manchukuo in northeastern China during the 1930s and early 1940s.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Baoji
Triple: [Shaanxi Province, hasMajorCity, Baoji]
Generated description
Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Baoji
Target entity description: Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
  • A. Bozhou
    Bozhou is a historic city in northern Anhui Province, China, known as a major center of traditional Chinese medicine and ancient culture.
  • B. Yan'an
    Yan'an is a historic city in China's Shaanxi province that served as the Chinese Communist Party's revolutionary base and political center during the late 1930s and 1940s.
  • C. Taian
    Taian is a prefecture-level city in eastern China's Shandong province, best known as the gateway to the sacred Mount Tai.
  • D. 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.
  • E. Xinjing
    Xinjing was the capital city of the Japanese puppet state of Manchukuo in northeastern China during the 1930s and early 1940s.
  • F. None of above. chosen

Provenance (5 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b645a081909dafdf7a32f2a389 completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0300207481908c8b91b83b2575bc completed March 8, 2026, 11:15 p.m.
NEDg Description generation batch_69ae039a7c948190b8b4b4c2045007d3 completed March 8, 2026, 11:17 p.m.
NED2 Entity disambiguation (via description) batch_69ae04253a80819092c112faddec1de1 completed March 8, 2026, 11:20 p.m.
Created at: March 4, 2026, 7:30 p.m.