Triple

T2939817
Position Surface form Disambiguated ID Type / Status
Subject Turkmenabat E79357 entity
Predicate formerName P65 FINISHED
Object Charjuy
Charjuy is the former name of the city now known as Turkmenabat, a major urban center in eastern Turkmenistan.
 E316605 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: Charjuy | Statement: [Turkmenabat, formerName, Charjuy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Charjuy
Context triple: [Turkmenabat, formerName, Charjuy]
  • A. Charcas
    Charcas is the former name of the Bolivian city now known as Sucre, a historic colonial center and constitutional capital of Bolivia.
  • B. Chiguayante
    Chiguayante is a Chilean city located near Concepción, known as part of the Greater Concepción metropolitan area in the south-central part of the country.
  • C. Pasochoa
    Pasochoa is an extinct volcanic mountain in Ecuador known for its lush cloud forests and rich biodiversity within a protected ecological reserve.
  • D. Huambisa
    Huambisa is an indigenous Jivaroan language spoken by the Huambisa people of the northern Peruvian Amazon.
  • E. Pitalito
    Pitalito is a major town and coffee-producing hub in southern Colombia, known as one of the country’s most important centers for high-quality coffee.
  • 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: Charjuy
Triple: [Turkmenabat, formerName, Charjuy]
Generated description
Charjuy is the former name of the city now known as Turkmenabat, a major urban center in eastern Turkmenistan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Charjuy
Target entity description: Charjuy is the former name of the city now known as Turkmenabat, a major urban center in eastern Turkmenistan.
  • A. Charcas
    Charcas is the former name of the Bolivian city now known as Sucre, a historic colonial center and constitutional capital of Bolivia.
  • B. Chiguayante
    Chiguayante is a Chilean city located near Concepción, known as part of the Greater Concepción metropolitan area in the south-central part of the country.
  • C. Pasochoa
    Pasochoa is an extinct volcanic mountain in Ecuador known for its lush cloud forests and rich biodiversity within a protected ecological reserve.
  • D. Huambisa
    Huambisa is an indigenous Jivaroan language spoken by the Huambisa people of the northern Peruvian Amazon.
  • E. Pitalito
    Pitalito is a major town and coffee-producing hub in southern Colombia, known as one of the country’s most important centers for high-quality coffee.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad986d9a248190927efc1a0c7d247f completed March 8, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108d4e5408190a0dd3728c5cf6a47 completed March 11, 2026, 6:16 a.m.
NEDg Description generation batch_69b10ccadf608190b2032ebb51271c90 completed March 11, 2026, 6:33 a.m.
NED2 Entity disambiguation (via description) batch_69b10d3e846481909a4342d844071040 completed March 11, 2026, 6:35 a.m.
Created at: March 8, 2026, 2:56 p.m.