Triple

T29472211
Position Surface form Disambiguated ID Type / Status
Subject Джентльмены удачи E747539 entity
Predicate монтажёр P167216 FINISHED
Object Наталия Анисимова
Наталия Анисимова — советский и российский киномонтажёр, работавшая над рядом известных фильмов, включая комедию «Джентльмены удачи».
 E2054671 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: Наталия Анисимова | Statement: [Джентльмены удачи, монтажёр, Наталия Анисимова]
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: Наталия Анисимова
Triple: [Джентльмены удачи, монтажёр, Наталия Анисимова]
Generated description
Наталия Анисимова — советский и российский киномонтажёр, работавшая над рядом известных фильмов, включая комедию «Джентльмены удачи».
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: монтажёр
Context triple: [Джентльмены удачи, монтажёр, Наталия Анисимова]
  • A. architectOfRenovation
    Indicates that one entity is the architect responsible for designing or overseeing the renovation of another entity.
  • B. notableContractor
    Indicates that one entity serves as a contractor for another in a way that is distinguished, prominent, or otherwise noteworthy.
  • C. hasCraftsman
    Indicates that one entity serves as the craftsman, maker, or artisan responsible for creating, building, or crafting another entity.
  • D. laterEngineer
    Indicates that one entity becomes an engineer at a later time than another entity.
  • E. crewMate
    Indicates that two entities are members of the same crew or team, sharing a common group affiliation or working together in a joint capacity.
  • F. None of above. chosen

Provenance (7 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_69f0bd42cf308190bb01b20bc5b7c2d0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66babf5e08190b8e1007546f3881a completed May 2, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a359583c21c819083b2c2d5ac15ad11 completed June 19, 2026, 7:16 p.m.
NEDg Description generation batch_6a35a07b378c81909c246bc347c47ee3 completed June 19, 2026, 8:03 p.m.
NED2 Entity disambiguation (via description) batch_6a35a103368881908241e8cc960d871d completed June 19, 2026, 8:05 p.m.
PD Predicate disambiguation batch_69f66339175c819080bd70f0ff7057b1 completed May 2, 2026, 8:48 p.m.
PDg Predicate description generation batch_69f663ff176c8190aaadb475f75daee4 completed May 2, 2026, 8:52 p.m.
Created at: April 28, 2026, 3:58 p.m.