Triple

T689187
Position Surface form Disambiguated ID Type / Status
Subject Anhui E13352 entity
Predicate containsCity P294 FINISHED
Object Tongling
Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
 E160108 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: Tongling | Statement: [Anhui, containsCity, Tongling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tongling
Context triple: [Anhui, containsCity, Tongling]
  • A. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • B. Anqing
    Anqing is a prefecture-level city in southwestern Anhui Province, China, known historically as a regional political and military center along the Yangtze River.
  • C. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • D. Tiāntán
    Tiāntán is the Chinese pinyin name for the Temple of Heaven, a historic imperial religious complex in Beijing where Ming and Qing dynasty emperors performed annual ceremonies to pray for good harvests.
  • E. Xianning
    Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
  • 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: Tongling
Triple: [Anhui, containsCity, Tongling]
Generated description
Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tongling
Target entity description: Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • A. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • B. Anqing
    Anqing is a prefecture-level city in southwestern Anhui Province, China, known historically as a regional political and military center along the Yangtze River.
  • C. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • D. Tiāntán
    Tiāntán is the Chinese pinyin name for the Temple of Heaven, a historic imperial religious complex in Beijing where Ming and Qing dynasty emperors performed annual ceremonies to pray for good harvests.
  • E. Xianning
    Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
  • 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_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a09669e4819089753204772e1fdd completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69acddf440848190aa5019ffcedd4859 completed March 8, 2026, 2:24 a.m.
NEDg Description generation batch_69acdefbfb108190a88d56c4e9f9e6b3 completed March 8, 2026, 2:29 a.m.
NED2 Entity disambiguation (via description) batch_69acdfeb4ca481909347f98cf78cf6a0 completed March 8, 2026, 2:33 a.m.
Created at: March 1, 2026, 7:36 p.m.