Triple

T6352041
Position Surface form Disambiguated ID Type / Status
Subject Grozny railway station E142894 entity
Predicate connectsTo P845 FINISHED
Object Mineralnye Vody
Mineralnye Vody is a town in Russia’s Stavropol Krai known as a key transport hub in the North Caucasus, particularly for its railway and airport connections.
 E586487 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: Mineralnye Vody | Statement: [Grozny railway station, connectsTo, Mineralnye Vody]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mineralnye Vody
Context triple: [Grozny railway station, connectsTo, Mineralnye Vody]
  • A. Kislovodsk
    Kislovodsk is a Russian spa and resort city in the North Caucasus, renowned for its mineral springs and mountainous surroundings.
  • B. Borjomi
    Borjomi is a Georgian resort town famous for its mineral water springs and scenic location in the Borjomi Gorge.
  • C. Torzhok
    Torzhok is a historic town in western Russia known for its medieval architecture, traditional goldwork embroidery, and location on the Tvertsa River.
  • D. Tskaltubo
    Tskaltubo is a spa town in western Georgia renowned for its radon-carbonate mineral springs and Soviet-era sanatoriums.
  • E. Krasnogorsk
    Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside Moscow.
  • 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: Mineralnye Vody
Triple: [Grozny railway station, connectsTo, Mineralnye Vody]
Generated description
Mineralnye Vody is a town in Russia’s Stavropol Krai known as a key transport hub in the North Caucasus, particularly for its railway and airport connections.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mineralnye Vody
Target entity description: Mineralnye Vody is a town in Russia’s Stavropol Krai known as a key transport hub in the North Caucasus, particularly for its railway and airport connections.
  • A. Kislovodsk
    Kislovodsk is a Russian spa and resort city in the North Caucasus, renowned for its mineral springs and mountainous surroundings.
  • B. Borjomi
    Borjomi is a Georgian resort town famous for its mineral water springs and scenic location in the Borjomi Gorge.
  • C. Torzhok
    Torzhok is a historic town in western Russia known for its medieval architecture, traditional goldwork embroidery, and location on the Tvertsa River.
  • D. Tskaltubo
    Tskaltubo is a spa town in western Georgia renowned for its radon-carbonate mineral springs and Soviet-era sanatoriums.
  • E. Krasnogorsk
    Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside Moscow.
  • 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_69c008d6dcbc8190aa1c2f1fd8916b42 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067dd3c74819085a164b750094c46 completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c604546ed08190bb1c89bc5461f5cd completed March 27, 2026, 4:15 a.m.
NEDg Description generation batch_69c6059ad89881909599c61f293791cc completed March 27, 2026, 4:20 a.m.
NED2 Entity disambiguation (via description) batch_69c60651d8d4819097c953b15f0aafc4 completed March 27, 2026, 4:23 a.m.
Created at: March 22, 2026, 4:31 p.m.