Triple

T4932644
Position Surface form Disambiguated ID Type / Status
Subject Kirenga River E110732 entity
Predicate hasSettlementOnBank P1010 FINISHED
Object Kirensk
Kirensk is a small town in Irkutsk Oblast, Russia, serving as a local administrative and transport hub in Eastern Siberia.
 E481845 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: Kirensk | Statement: [Kirenga River, hasSettlementOnBank, Kirensk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kirensk
Context triple: [Kirenga River, hasSettlementOnBank, Kirensk]
  • A. Kirovakan
    Kirovakan is the former name of Vanadzor, a major industrial city in northern Armenia.
  • B. Kievskaya
    Kievskaya is a prominent Moscow Metro station complex known for its ornate, Ukrainian-themed architecture and role as a major transfer hub.
  • C. Kalininsk
    Kalininsk is a small town in southwestern Russia known for its agricultural surroundings and location within Saratov Oblast on the Volga River region.
  • D. Kurskaya
    Kurskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, serving as a major transfer hub in the city’s rapid transit network.
  • E. Voskresensk
    Voskresensk is a town in Moscow Oblast, Russia, known for its industrial base and strong ice hockey tradition.
  • 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: Kirensk
Triple: [Kirenga River, hasSettlementOnBank, Kirensk]
Generated description
Kirensk is a small town in Irkutsk Oblast, Russia, serving as a local administrative and transport hub in Eastern Siberia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kirensk
Target entity description: Kirensk is a small town in Irkutsk Oblast, Russia, serving as a local administrative and transport hub in Eastern Siberia.
  • A. Kirovakan
    Kirovakan is the former name of Vanadzor, a major industrial city in northern Armenia.
  • B. Kievskaya
    Kievskaya is a prominent Moscow Metro station complex known for its ornate, Ukrainian-themed architecture and role as a major transfer hub.
  • C. Kalininsk
    Kalininsk is a small town in southwestern Russia known for its agricultural surroundings and location within Saratov Oblast on the Volga River region.
  • D. Kurskaya
    Kurskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, serving as a major transfer hub in the city’s rapid transit network.
  • E. Voskresensk
    Voskresensk is a town in Moscow Oblast, Russia, known for its industrial base and strong ice hockey tradition.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd70652d988190ba4a493db510952e completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77b41c4c8190b4f714334242bc9b completed March 21, 2026, 10:49 a.m.
NEDg Description generation batch_69be7b9611a881908e83086719406145 completed March 21, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69be7ce630248190b274547eaa15fe85 completed March 21, 2026, 11:11 a.m.
Created at: March 20, 2026, 1:30 p.m.