Triple

T17954964
Position Surface form Disambiguated ID Type / Status
Subject Щёкинский район E448920 entity
Predicate hasNeighboringRegion P17964 FINISHED
Object Тула
Тула — крупный промышленный и культурный центр России, известный как исторический город-оружейник и родина тульского пряника.
 E1348237 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: Тула | Statement: [Щёкинский район, hasNeighboringRegion, Тула]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Тула
Context triple: [Щёкинский район, hasNeighboringRegion, Тула]
  • A. Tambov
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • B. Ryazan
    Ryazan is a historic city in western Russia known for its medieval kremlin, role as a regional cultural and economic center, and legacy as one of the country’s oldest urban settlements.
  • 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. Volokolamsk
    Volokolamsk is a historic town in western Russia, located northwest of Moscow and known for its medieval origins and role in regional trade and defense.
  • E. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation 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: Тула
Triple: [Щёкинский район, hasNeighboringRegion, Тула]
Generated description
Тула — крупный промышленный и культурный центр России, известный как исторический город-оружейник и родина тульского пряника.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Тула
Target entity description: Тула — крупный промышленный и культурный центр России, известный как исторический город-оружейник и родина тульского пряника.
  • A. Tambov
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • B. Ryazan
    Ryazan is a historic city in western Russia known for its medieval kremlin, role as a regional cultural and economic center, and legacy as one of the country’s oldest urban settlements.
  • 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. Volokolamsk
    Volokolamsk is a historic town in western Russia, located northwest of Moscow and known for its medieval origins and role in regional trade and defense.
  • E. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4afaf1ddc8190b480147ac35a4912 completed April 19, 2026, 10:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05829917e4819093dc8ae6ed4cdb6a completed May 14, 2026, 8:06 a.m.
NEDg Description generation batch_6a05885e976c81909ca84e84920dcc2d completed May 14, 2026, 8:31 a.m.
NED2 Entity disambiguation (via description) batch_6a0588d5399081908a959f47a7ea74d7 completed May 14, 2026, 8:33 a.m.
Created at: April 10, 2026, 10:21 a.m.