Triple

T2960345
Position Surface form Disambiguated ID Type / Status
Subject Balkanabat E80031 entity
Predicate formerName P65 FINISHED
Object Nebit-Dag
Nebit-Dag is the former name of Balkanabat, a city in western Turkmenistan known for its role in the country’s oil and gas industry.
 E313886 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: Nebit-Dag | Statement: [Balkanabat, formerName, Nebit-Dag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nebit-Dag
Context triple: [Balkanabat, formerName, Nebit-Dag]
  • A. Gardabani
    Gardabani is a town in southeastern Georgia known for its role as an industrial and energy hub within the Kvemo Kartli region.
  • B. Marḥeshvan
    Marḥeshvan is the eighth month of the Hebrew calendar, traditionally noted for having no major Jewish holidays.
  • C. Kharabali
    Kharabali is a town in southern Russia that serves as an administrative and economic center within Astrakhan Oblast.
  • D. Tahawus
    Tahawus is a remote hamlet in New York’s Adirondack Mountains known for its historic iron mining operations and proximity to High Peaks wilderness areas.
  • E. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • 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: Nebit-Dag
Triple: [Balkanabat, formerName, Nebit-Dag]
Generated description
Nebit-Dag is the former name of Balkanabat, a city in western Turkmenistan known for its role in the country’s oil and gas industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nebit-Dag
Target entity description: Nebit-Dag is the former name of Balkanabat, a city in western Turkmenistan known for its role in the country’s oil and gas industry.
  • A. Gardabani
    Gardabani is a town in southeastern Georgia known for its role as an industrial and energy hub within the Kvemo Kartli region.
  • B. Marḥeshvan
    Marḥeshvan is the eighth month of the Hebrew calendar, traditionally noted for having no major Jewish holidays.
  • C. Kharabali
    Kharabali is a town in southern Russia that serves as an administrative and economic center within Astrakhan Oblast.
  • D. Tahawus
    Tahawus is a remote hamlet in New York’s Adirondack Mountains known for its historic iron mining operations and proximity to High Peaks wilderness areas.
  • E. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • 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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad992dd4248190b5f3d4f342593b8c completed March 8, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc923d888190a68075dfaa9e90b2 completed March 11, 2026, 5:24 a.m.
NEDg Description generation batch_69b0fd7d1cc88190a4f533a92d7e6de3 completed March 11, 2026, 5:28 a.m.
NED2 Entity disambiguation (via description) batch_69b0fde74b608190b59da720c90adfeb completed March 11, 2026, 5:30 a.m.
Created at: March 8, 2026, 2:57 p.m.