Triple

T552178
Position Surface form Disambiguated ID Type / Status
Subject Hebei E11863 entity
Predicate hasMajorCity P316 FINISHED
Object Tangshan
Tangshan is a major industrial city in northern China, historically known for its coal mining, steel production, and the devastating 1976 earthquake.
 E123029 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: Tangshan | Statement: [Hebei, hasMajorCity, Tangshan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tangshan
Context triple: [Hebei, hasMajorCity, Tangshan]
  • A. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • B. Anyang
    Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
  • C. Shijiazhuang
    Shijiazhuang is the capital and largest city of Hebei Province in northern China, known as a major industrial and transportation hub.
  • D. Ma’anshan
    Ma’anshan is an industrial city in eastern China known for its steel production and location along the lower Yangtze River.
  • E. Beihai
    Beihai is a coastal city in China's Guangxi Zhuang Autonomous Region, known for its beaches, maritime trade, and the scenic Silver Beach tourist area.
  • 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: Tangshan
Triple: [Hebei, hasMajorCity, Tangshan]
Generated description
Tangshan is a major industrial city in northern China, historically known for its coal mining, steel production, and the devastating 1976 earthquake.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tangshan
Target entity description: Tangshan is a major industrial city in northern China, historically known for its coal mining, steel production, and the devastating 1976 earthquake.
  • A. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • B. Anyang
    Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
  • C. Shijiazhuang
    Shijiazhuang is the capital and largest city of Hebei Province in northern China, known as a major industrial and transportation hub.
  • D. Ma’anshan
    Ma’anshan is an industrial city in eastern China known for its steel production and location along the lower Yangtze River.
  • E. Beihai
    Beihai is a coastal city in China's Guangxi Zhuang Autonomous Region, known for its beaches, maritime trade, and the scenic Silver Beach tourist area.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499047bd4819089ca8345f1b6e46c completed March 1, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4279b23c8190854732f4d6d5d6cd completed March 7, 2026, 3:21 p.m.
NEDg Description generation batch_69ac430384ec8190a307c895bb12a122 completed March 7, 2026, 3:23 p.m.
NED2 Entity disambiguation (via description) batch_69ac437b62bc8190abfb721c570b4768 completed March 7, 2026, 3:25 p.m.
Created at: March 1, 2026, 7:32 p.m.