Triple

T10169856
Position Surface form Disambiguated ID Type / Status
Subject Voronezh River E235301 entity
Predicate hasCityOnBank P7935 FINISHED
Object Lipetsk
Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
 E903510 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: Lipetsk | Statement: [Voronezh River, hasCityOnBank, Lipetsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lipetsk
Context triple: [Voronezh River, hasCityOnBank, Lipetsk]
  • A. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • B. Izhevsk
    Izhevsk is a major industrial city in western Russia, best known as a center of arms manufacturing and the capital of the Udmurt Republic.
  • C. Tambov
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • D. Penza
    Penza is a city in western Russia known as a regional cultural and industrial center.
  • E. Ryazhsk
    Ryazhsk is a historic town in Ryazan Oblast, Russia, known as a former local administrative center dating back to the Russian Empire.
  • 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: Lipetsk
Triple: [Voronezh River, hasCityOnBank, Lipetsk]
Generated description
Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lipetsk
Target entity description: Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
  • A. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • B. Izhevsk
    Izhevsk is a major industrial city in western Russia, best known as a center of arms manufacturing and the capital of the Udmurt Republic.
  • C. Tambov
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • D. Penza
    Penza is a city in western Russia known as a regional cultural and industrial center.
  • E. Ryazhsk
    Ryazhsk is a historic town in Ryazan Oblast, Russia, known as a former local administrative center dating back to the Russian Empire.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec9ba56481908b5265aea8ea8cbe completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3e686db808190a2aa975a20e69696 completed April 18, 2026, 8:16 p.m.
NEDg Description generation batch_69e3f2c889dc81909a04c1db0509e3d9 completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f4746dbc8190a0e28202ad5e6b4f completed April 18, 2026, 9:15 p.m.
Created at: March 30, 2026, 9:10 p.m.