Triple

T3109985
Position Surface form Disambiguated ID Type / Status
Subject Shanxi Province E64927 entity
Predicate hasMajorCity P316 FINISHED
Object Yangquan
Yangquan is an industrial city in northern China known for its coal mining and heavy industry within Shanxi Province.
 E341834 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: Yangquan | Statement: [Shanxi Province, hasMajorCity, Yangquan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yangquan
Context triple: [Shanxi Province, hasMajorCity, Yangquan]
  • A. Datong
    Datong is a historic industrial city in northern China known for its coal production and nearby cultural landmarks such as the Yungang Grottoes.
  • B. Chifeng
    Chifeng is a prefecture-level city in southeastern Inner Mongolia, China, known for its mix of grassland, forest, and historical sites linked to ancient nomadic cultures.
  • C. Baotou
    Baotou is a major industrial city in Inner Mongolia, China, known especially for its steel production and nearby rare earth mineral processing.
  • D. Shuozhou
    Shuozhou is a prefecture-level city in northern China known for its coal resources and historical sites within Shanxi Province.
  • E. Changzhi
    Changzhi is a major city in southeastern Shanxi Province, China, known as a regional industrial and transportation hub with a long historical and cultural heritage.
  • 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: Yangquan
Triple: [Shanxi Province, hasMajorCity, Yangquan]
Generated description
Yangquan is an industrial city in northern China known for its coal mining and heavy industry within Shanxi Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yangquan
Target entity description: Yangquan is an industrial city in northern China known for its coal mining and heavy industry within Shanxi Province.
  • A. Datong
    Datong is a historic industrial city in northern China known for its coal production and nearby cultural landmarks such as the Yungang Grottoes.
  • B. Chifeng
    Chifeng is a prefecture-level city in southeastern Inner Mongolia, China, known for its mix of grassland, forest, and historical sites linked to ancient nomadic cultures.
  • C. Baotou
    Baotou is a major industrial city in Inner Mongolia, China, known especially for its steel production and nearby rare earth mineral processing.
  • D. Shuozhou
    Shuozhou is a prefecture-level city in northern China known for its coal resources and historical sites within Shanxi Province.
  • E. Changzhi
    Changzhi is a major city in southeastern Shanxi Province, China, known as a regional industrial and transportation hub with a long historical and cultural heritage.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada2a0ab2481908db50738ec3ad0fb completed March 8, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28e058d8c8190ae58d750ae4c2c0e completed March 12, 2026, 9:57 a.m.
NEDg Description generation batch_69b28fbaa3048190b42991ede51c6ca8 completed March 12, 2026, 10:04 a.m.
NED2 Entity disambiguation (via description) batch_69b2ab2315ec8190b27da4e41696a7e3 completed March 12, 2026, 12:01 p.m.
Created at: March 8, 2026, 3:04 p.m.