Triple

T15776446
Position Surface form Disambiguated ID Type / Status
Subject Tashkent Region E382503 entity
Predicate containsCity P294 FINISHED
Object Bekabad
Bekabad is an industrial city in eastern Uzbekistan known for its steel production and location along the Syr Darya River.
 E1176318 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: Bekabad | Statement: [Tashkent Region, containsCity, Bekabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bekabad
Context triple: [Tashkent Region, containsCity, Bekabad]
  • A. Bakhdida
    Bakhdida is a historically Assyrian Christian town in northern Iraq, known for its ancient churches and location in the Nineveh Plains near Mosul.
  • B. Bazarduzu
    Bazarduzu is the highest mountain in Azerbaijan, located in the Greater Caucasus range on the border with Russia.
  • C. Balakan
    Balakan is a town and district center in northwestern Azerbaijan, near the border with Georgia and Russia, known for its mountainous landscapes and agricultural production.
  • D. Kakabadse
    Kakabadse is a Georgian-origin surname notably borne by figures such as environmentalist Yolanda Kakabadse.
  • E. Keban
    Keban is a town in eastern Turkey located near the Euphrates River, known primarily for its proximity to the large hydroelectric Keban Dam.
  • 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: Bekabad
Triple: [Tashkent Region, containsCity, Bekabad]
Generated description
Bekabad is an industrial city in eastern Uzbekistan known for its steel production and location along the Syr Darya River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bekabad
Target entity description: Bekabad is an industrial city in eastern Uzbekistan known for its steel production and location along the Syr Darya River.
  • A. Bakhdida
    Bakhdida is a historically Assyrian Christian town in northern Iraq, known for its ancient churches and location in the Nineveh Plains near Mosul.
  • B. Bazarduzu
    Bazarduzu is the highest mountain in Azerbaijan, located in the Greater Caucasus range on the border with Russia.
  • C. Balakan
    Balakan is a town and district center in northwestern Azerbaijan, near the border with Georgia and Russia, known for its mountainous landscapes and agricultural production.
  • D. Kakabadse
    Kakabadse is a Georgian-origin surname notably borne by figures such as environmentalist Yolanda Kakabadse.
  • E. Keban
    Keban is a town in eastern Turkey located near the Euphrates River, known primarily for its proximity to the large hydroelectric Keban Dam.
  • 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_69d86da09a10819082fe9797b23e4664 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e05199cd8881909462462cec34d35a completed April 16, 2026, 3:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff909b467c819097ee87f51d2001da completed May 9, 2026, 7:52 p.m.
NEDg Description generation batch_69ff9277dc2881908fe0cd70e3d61f3f completed May 9, 2026, 8 p.m.
NED2 Entity disambiguation (via description) batch_69ff93745f508190927b79a5debead12 completed May 9, 2026, 8:05 p.m.
Created at: April 10, 2026, 4:47 a.m.