Triple

T13129744
Position Surface form Disambiguated ID Type / Status
Subject Vyborgsky District E311936 entity
Predicate containsSettlement P847 FINISHED
Object Udelnaya
Udelnaya is a residential neighborhood and railway station area in the northern part of Saint Petersburg, Russia.
 E1021975 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: Udelnaya | Statement: [Vyborgsky District, containsSettlement, Udelnaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Udelnaya
Context triple: [Vyborgsky District, containsSettlement, Udelnaya]
  • A. Udelar
    Udelar is Uruguay’s main public university, renowned for its central role in the country’s higher education, research, and cultural life.
  • B. Udjebten
    Udjebten was an ancient Egyptian queen of the Sixth Dynasty, likely one of the principal wives of Pharaoh Pepi II Neferkare.
  • C. Uddel
    Uddel is a village in the Dutch province of Gelderland, situated on the Veluwe and known for its rural character and surrounding forests and heathlands.
  • D. Uzlovaya
    Uzlovaya is a town in western Russia known as an industrial and railway hub within Tula Oblast.
  • E. Ulassai
    Ulassai is a small mountain village in central-eastern Sardinia, Italy, known for its dramatic limestone cliffs, waterfalls, and contemporary art installations linked to artist Maria Lai.
  • 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: Udelnaya
Triple: [Vyborgsky District, containsSettlement, Udelnaya]
Generated description
Udelnaya is a residential neighborhood and railway station area in the northern part of Saint Petersburg, Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Udelnaya
Target entity description: Udelnaya is a residential neighborhood and railway station area in the northern part of Saint Petersburg, Russia.
  • A. Udelar
    Udelar is Uruguay’s main public university, renowned for its central role in the country’s higher education, research, and cultural life.
  • B. Udjebten
    Udjebten was an ancient Egyptian queen of the Sixth Dynasty, likely one of the principal wives of Pharaoh Pepi II Neferkare.
  • C. Uddel
    Uddel is a village in the Dutch province of Gelderland, situated on the Veluwe and known for its rural character and surrounding forests and heathlands.
  • D. Uzlovaya
    Uzlovaya is a town in western Russia known as an industrial and railway hub within Tula Oblast.
  • E. Ulassai
    Ulassai is a small mountain village in central-eastern Sardinia, Italy, known for its dramatic limestone cliffs, waterfalls, and contemporary art installations linked to artist Maria Lai.
  • 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_69d806a9fe888190b081e2d9ea665d6c completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9819bfd348190a22d44f837877e1c completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e290c308819090ee4436c199b57c completed May 3, 2026, 5:52 a.m.
NEDg Description generation batch_69f6e397df5c8190a470fc5c226b027b completed May 3, 2026, 5:56 a.m.
NED2 Entity disambiguation (via description) batch_69f6e454f95c8190b023c5d141999dd8 completed May 3, 2026, 5:59 a.m.
Created at: April 9, 2026, 9:07 p.m.