Triple

T23159321
Position Surface form Disambiguated ID Type / Status
Subject Magaramkentsky District E578535 entity
Predicate administrativeCenter P1474 FINISHED
Object Magaramkent
Magaramkent is a rural locality in the Republic of Dagestan, Russia, serving as a local administrative and cultural hub in the region.
E1574320 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: Magaramkent | Statement: [Magaramkentsky District, administrativeCenter, Magaramkent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magaramkent
Context triple: [Magaramkentsky District, administrativeCenter, Magaramkent]
  • A. Homayunshahr
    Homayunshahr is a city in Iran best known as the birthplace of acclaimed filmmaker Asghar Farhadi.
  • B. Sheberghan
    Sheberghan is a city in northern Afghanistan that serves as a political and military stronghold of Uzbek leader Abdul Rashid Dostum.
  • C. Karashahr
    Karashahr is an ancient oasis town in Xinjiang, China, historically significant as a Silk Road hub and a key center of the Indo-European–speaking Tocharian culture.
  • D. Tokhi
    Tokhi is a prominent Pashtun tribe that forms part of the larger Ghilji tribal confederation in Afghanistan.
  • E. Sharaqpur
    Sharaqpur is a town in Pakistan’s Punjab province known for its religious significance and traditional Punjabi culture.
  • 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: Magaramkent
Triple: [Magaramkentsky District, administrativeCenter, Magaramkent]
Generated description
Magaramkent is a rural locality in the Republic of Dagestan, Russia, serving as a local administrative and cultural hub in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Magaramkent
Target entity description: Magaramkent is a rural locality in the Republic of Dagestan, Russia, serving as a local administrative and cultural hub in the region.
  • A. Homayunshahr
    Homayunshahr is a city in Iran best known as the birthplace of acclaimed filmmaker Asghar Farhadi.
  • B. Sheberghan
    Sheberghan is a city in northern Afghanistan that serves as a political and military stronghold of Uzbek leader Abdul Rashid Dostum.
  • C. Karashahr
    Karashahr is an ancient oasis town in Xinjiang, China, historically significant as a Silk Road hub and a key center of the Indo-European–speaking Tocharian culture.
  • D. Tokhi
    Tokhi is a prominent Pashtun tribe that forms part of the larger Ghilji tribal confederation in Afghanistan.
  • E. Sharaqpur
    Sharaqpur is a town in Pakistan’s Punjab province known for its religious significance and traditional Punjabi culture.
  • 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_69e245fc75348190a0288401044c8af8 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18eff965081909aaa6fc1910293e2 completed April 29, 2026, 4:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c30a009a88190ace5fe645f0e9d23 completed May 19, 2026, 9:42 a.m.
NEDg Description generation batch_6a0c3433083081909b486004ed8ae017 completed May 19, 2026, 9:58 a.m.
NED2 Entity disambiguation (via description) batch_6a0c352416508190a08f1d46ef3c4916 completed May 19, 2026, 10:02 a.m.
Created at: April 17, 2026, 4:02 p.m.