Triple

T7345105
Position Surface form Disambiguated ID Type / Status
Subject Grand Hotel E169356 entity
Predicate character P662 FINISHED
Object Grusinskaya
Grusinskaya is a fading but still celebrated Russian ballerina whose loneliness and vulnerability are central to the drama of the film "Grand Hotel."
 E668179 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: Grusinskaya | Statement: [Grand Hotel, character, Grusinskaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Grusinskaya
Context triple: [Grand Hotel, character, Grusinskaya]
  • A. Dobryninskaya
    Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
  • B. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • C. Taganskaya
    Taganskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, known for its ornate post-war Stalinist architecture and decorative ceramic panels.
  • D. Mishaninskaya
    Mishaninskaya is a rural locality in Russia best known as the birthplace of the polymath and scientist Mikhail Lomonosov.
  • E. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • 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: Grusinskaya
Triple: [Grand Hotel, character, Grusinskaya]
Generated description
Grusinskaya is a fading but still celebrated Russian ballerina whose loneliness and vulnerability are central to the drama of the film "Grand Hotel."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Grusinskaya
Target entity description: Grusinskaya is a fading but still celebrated Russian ballerina whose loneliness and vulnerability are central to the drama of the film "Grand Hotel."
  • A. Dobryninskaya
    Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
  • B. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • C. Taganskaya
    Taganskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, known for its ornate post-war Stalinist architecture and decorative ceramic panels.
  • D. Mishaninskaya
    Mishaninskaya is a rural locality in Russia best known as the birthplace of the polymath and scientist Mikhail Lomonosov.
  • E. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • 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_69c68a57710481909f0c1f3c6ebdb6f2 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0eeb30081909d25704ac9b49d0e completed March 27, 2026, 9:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c43f24881908a434773dfd79892 completed March 28, 2026, 8:38 p.m.
NEDg Description generation batch_69c83da7ebd48190863691f70338f485 completed March 28, 2026, 8:44 p.m.
NED2 Entity disambiguation (via description) batch_69c83e0acdd881908d6846a3a836720a completed March 28, 2026, 8:46 p.m.
Created at: March 27, 2026, 3:05 p.m.