Triple

T9461461
Position Surface form Disambiguated ID Type / Status
Subject سيحون E228154 entity
Predicate يمر_قرب P350 FINISHED
Object مدينة قراغندي
مدينة قراغندي هي مدينة تقع في منطقة آسيا الوسطى قرب نهر سيحون التاريخي، وتعد مركزاً محلياً للحياة السكانية والتجارة.
 E800946 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 قراغندي | Statement: [سيحون, يمر_قرب, مدينة قراغندي]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: مدينة قراغندي
Context triple: [سيحون, يمر_قرب, مدينة قراغندي]
  • A. Stolica
    Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
  • B. Elizavetgrad
    Elizavetgrad was the former name of the city now known as Kropyvnytskyi, a regional center in central Ukraine that was part of the Russian Empire at the time of Grigory Zinoviev’s birth.
  • C. Kirovakan
    Kirovakan is the former name of Vanadzor, a major industrial city in northern Armenia.
  • D. Lugos
    Lugos is a town in present-day Romania, historically part of the Austro-Hungarian Empire, known as the birthplace of actor Bela Lugosi.
  • E. Kilkís
    Kilkís is a town in northern Greece that serves as an important local center within the region of Central Macedonia.
  • 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 قراغندي
Triple: [سيحون, يمر_قرب, مدينة قراغندي]
Generated description
مدينة قراغندي هي مدينة تقع في منطقة آسيا الوسطى قرب نهر سيحون التاريخي، وتعد مركزاً محلياً للحياة السكانية والتجارة.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: مدينة قراغندي
Target entity description: مدينة قراغندي هي مدينة تقع في منطقة آسيا الوسطى قرب نهر سيحون التاريخي، وتعد مركزاً محلياً للحياة السكانية والتجارة.
  • A. Stolica
    Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
  • B. Elizavetgrad
    Elizavetgrad was the former name of the city now known as Kropyvnytskyi, a regional center in central Ukraine that was part of the Russian Empire at the time of Grigory Zinoviev’s birth.
  • C. Kirovakan
    Kirovakan is the former name of Vanadzor, a major industrial city in northern Armenia.
  • D. Lugos
    Lugos is a town in present-day Romania, historically part of the Austro-Hungarian Empire, known as the birthplace of actor Bela Lugosi.
  • E. Kilkís
    Kilkís is a town in northern Greece that serves as an important local center within the region of Central Macedonia.
  • 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.