Triple

T15552059
Position Surface form Disambiguated ID Type / Status
Subject Principality of Trubchevsk E370772 entity
Predicate capital P234 FINISHED
Object Trubchevsk
Trubchevsk is a historic town in western Russia, known as a former medieval center and namesake of the Principality of Trubchevsk.
 E1253472 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: Trubchevsk | Statement: [Principality of Trubchevsk, capital, Trubchevsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Trubchevsk
Context triple: [Principality of Trubchevsk, capital, Trubchevsk]
  • A. Borisoglebsk
    Borisoglebsk is a small Russian city known for its historical architecture and location on the Vorona River in southwestern Russia.
  • B. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • C. Novozybkov
    Novozybkov is a town in western Russia known as a local administrative and economic center near the borders with Belarus and Ukraine.
  • D. Kovrov
    Kovrov is an industrial city in western Russia known for its machine-building and arms manufacturing industries.
  • E. Zaraysk
    Zaraysk is a historic town in Moscow Oblast, Russia, known for its well-preserved medieval kremlin and role as a former regional administrative center.
  • 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: Trubchevsk
Triple: [Principality of Trubchevsk, capital, Trubchevsk]
Generated description
Trubchevsk is a historic town in western Russia, known as a former medieval center and namesake of the Principality of Trubchevsk.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Trubchevsk
Target entity description: Trubchevsk is a historic town in western Russia, known as a former medieval center and namesake of the Principality of Trubchevsk.
  • A. Borisoglebsk
    Borisoglebsk is a small Russian city known for its historical architecture and location on the Vorona River in southwestern Russia.
  • B. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • C. Novozybkov
    Novozybkov is a town in western Russia known as a local administrative and economic center near the borders with Belarus and Ukraine.
  • D. Kovrov
    Kovrov is an industrial city in western Russia known for its machine-building and arms manufacturing industries.
  • E. Zaraysk
    Zaraysk is a historic town in Moscow Oblast, Russia, known for its well-preserved medieval kremlin and role as a former regional administrative center.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a9551288190a583e8291c35f521 completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a014819dfbc8190b39a10647f9ba64c completed May 11, 2026, 3:08 a.m.
NEDg Description generation batch_6a0148d819f88190a201a31fdcd37b1c completed May 11, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_6a01493587948190b1a9f7ece8fcf072 completed May 11, 2026, 3:12 a.m.
Created at: April 10, 2026, 4:08 a.m.