Triple

T30436213
Position Surface form Disambiguated ID Type / Status
Subject Дом Советов РСФСР E774317 entity
Predicate расположенВРайонеГорода P83410 FINISHED
Object Пресненский район Москвы
Пресненский район Москвы — это центральный и один из наиболее престижных районов столицы, известный деловыми центрами, исторической застройкой и важными административными и культурными объектами.
 E1946197 NE FINISHED

How this triple was built (3 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: Пресненский район Москвы | Statement: [Дом Советов РСФСР, расположенВРайонеГорода, Пресненский район Москвы]
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: Пресненский район Москвы
Triple: [Дом Советов РСФСР, расположенВРайонеГорода, Пресненский район Москвы]
Generated description
Пресненский район Москвы — это центральный и один из наиболее престижных районов столицы, известный деловыми центрами, исторической застройкой и важными административными и культурными объектами.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: расположенВРайонеГорода
Context triple: [Дом Советов РСФСР, расположенВРайонеГорода, Пресненский район Москвы]
  • A. расположенаНа
    Indicates that one entity is located on the surface or area of another entity.
  • B. locatedIn
    Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
  • C. locatedInRegionalDistrict chosen
    Indicates that one entity is geographically situated within the boundaries of a specified regional district.
  • D. находитсяК
    Indicates that one entity is located at, in, or near another entity.
  • E. areLocatedAt
    Indicates that one or more entities occupy or exist at a specific location or place.
  • F. None of above.

Provenance (6 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_69f22492d2a88190995ce8745d9becaa completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f697eabb048190bc01a830f14942c6 completed May 3, 2026, 12:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a293887bbfc8190a8b411f45b0ae825 completed June 10, 2026, 10:12 a.m.
NEDg Description generation batch_6a29397f80108190b735df8c27bed113 completed June 10, 2026, 10:16 a.m.
NED2 Entity disambiguation (via description) batch_6a2939f6054c8190916e6b8cbdf98c55 completed June 10, 2026, 10:18 a.m.
PD Predicate disambiguation batch_69f69664142c8190bc695501056b0236 completed May 3, 2026, 12:27 a.m.
Created at: April 29, 2026, 8:07 p.m.