Triple

T5599195
Position Surface form Disambiguated ID Type / Status
Subject Jilin Province E147072 entity
Predicate containsCity P294 FINISHED
Object Tonghua
Tonghua is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, pharmaceutical industry, and role as a regional transportation hub.
 E536849 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: Tonghua | Statement: [Jilin Province, containsCity, Tonghua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tonghua
Context triple: [Jilin Province, containsCity, Tonghua]
  • A. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • B. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • C. Bocheng
    Bocheng is a Chinese given name most notably borne by the prominent Communist military leader and strategist Liu Bocheng.
  • D. Lüshun
    Lüshun is a strategically important port city in northeastern China, historically known as Port Arthur and noted for its role in several major conflicts.
  • E. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • 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: Tonghua
Triple: [Jilin Province, containsCity, Tonghua]
Generated description
Tonghua is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, pharmaceutical industry, and role as a regional transportation hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tonghua
Target entity description: Tonghua is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, pharmaceutical industry, and role as a regional transportation hub.
  • A. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • B. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • C. Bocheng
    Bocheng is a Chinese given name most notably borne by the prominent Communist military leader and strategist Liu Bocheng.
  • D. Lüshun
    Lüshun is a strategically important port city in northeastern China, historically known as Port Arthur and noted for its role in several major conflicts.
  • E. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • 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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020d82870819087f9591b5a1021ce completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d3be1bc8190a5cdc1bf694356a6 completed March 22, 2026, 8:12 p.m.
NEDg Description generation batch_69c04e88680c8190845723f52c060fb7 completed March 22, 2026, 8:18 p.m.
NED2 Entity disambiguation (via description) batch_69c04f7856848190a835c3ee0a32f649 completed March 22, 2026, 8:22 p.m.
Created at: March 22, 2026, 3:38 p.m.