Triple

T9461460
Position Surface form Disambiguated ID Type / Status
Subject سيحون E228154 entity
Predicate يمر_قرب P350 FINISHED
Object مدينة شيمكنت
مدينة شيمكنت هي ثالث أكبر مدن كازاخستان ومركز صناعي وتجاري مهم في جنوب البلاد.
 E800945 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: مدينة شيمكنت | Statement: [سيحون, يمر_قرب, مدينة شيمكنت]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: مدينة شيمكنت
Context triple: [سيحون, يمر_قرب, مدينة شيمكنت]
  • A. Anyang
    Anyang is a mid-sized South Korean city in the Seoul Capital Area known for its residential districts, light industry, and proximity to central Seoul.
  • 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. Taishan city
    Taishan city is a county-level coastal city in Guangdong Province, China, known for its overseas Chinese heritage and nearby islands such as Shangchuan Island.
  • D. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • E. Kim Chaek City
    Kim Chaek City is an industrial port city in North Hamgyong Province, North Korea, named in honor of the Korean War general and politician Kim Chaek.
  • 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: مدينة شيمكنت
Triple: [سيحون, يمر_قرب, مدينة شيمكنت]
Generated description
مدينة شيمكنت هي ثالث أكبر مدن كازاخستان ومركز صناعي وتجاري مهم في جنوب البلاد.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: مدينة شيمكنت
Target entity description: مدينة شيمكنت هي ثالث أكبر مدن كازاخستان ومركز صناعي وتجاري مهم في جنوب البلاد.
  • A. Anyang
    Anyang is a mid-sized South Korean city in the Seoul Capital Area known for its residential districts, light industry, and proximity to central Seoul.
  • 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. Taishan city
    Taishan city is a county-level coastal city in Guangdong Province, China, known for its overseas Chinese heritage and nearby islands such as Shangchuan Island.
  • D. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • E. Kim Chaek City
    Kim Chaek City is an industrial port city in North Hamgyong Province, North Korea, named in honor of the Korean War general and politician Kim Chaek.
  • 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_69ca843b123881909b0e60028475d12d completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7fcc8b1881908aa6ee13ab195330 completed April 1, 2026, 8:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1229ec9448190bac9b7a38e030833 completed April 4, 2026, 2:39 p.m.
NEDg Description generation batch_69d1245db2e48190a56a797a681316d9 completed April 4, 2026, 2:46 p.m.
NED2 Entity disambiguation (via description) batch_69d124c2a48c819098a24dd2aac734e1 completed April 4, 2026, 2:48 p.m.
Created at: March 30, 2026, 7:52 p.m.