Triple
T10689661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuznetsky Most |
E251975
|
entity |
| Predicate | architect |
P184
|
FINISHED |
| Object |
N. Samoylova
N. Samoylova is an architect known for work on projects along Moscow’s historic Kuznetsky Most street.
|
E879230
|
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: N. Samoylova | Statement: [Kuznetsky Most, architect, N. Samoylova]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: N. Samoylova Context triple: [Kuznetsky Most, architect, N. Samoylova]
-
A.
N. Shurygina
N. Shurygina is an architect known for contributing to the design and development of the Novogireyevo district in Moscow.
-
B.
Yu. Kolesnikova
Yu. Kolesnikova is an architect known for designing the Bagrationovskaya station in the Moscow Metro system.
-
C.
Tatyana Samoylova
Tatyana Samoylova was a celebrated Soviet and Russian film actress best known internationally for her poignant leading role in the acclaimed World War II drama "The Cranes Are Flying."
-
D.
Olga Naumova
Olga Naumova was the wife of renowned Russian-born conductor and double-bassist Serge Koussevitzky, accompanying him through the early part of his musical career.
-
E.
Marfa Lapkina
Marfa Lapkina was a Soviet actress best known for her leading role in Sergei Eisenstein’s silent film "The General Line" (also known as "Old and New").
- 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: N. Samoylova Triple: [Kuznetsky Most, architect, N. Samoylova]
Generated description
N. Samoylova is an architect known for work on projects along Moscow’s historic Kuznetsky Most street.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: N. Samoylova Target entity description: N. Samoylova is an architect known for work on projects along Moscow’s historic Kuznetsky Most street.
-
A.
N. Shurygina
N. Shurygina is an architect known for contributing to the design and development of the Novogireyevo district in Moscow.
-
B.
Yu. Kolesnikova
Yu. Kolesnikova is an architect known for designing the Bagrationovskaya station in the Moscow Metro system.
-
C.
Tatyana Samoylova
Tatyana Samoylova was a celebrated Soviet and Russian film actress best known internationally for her poignant leading role in the acclaimed World War II drama "The Cranes Are Flying."
-
D.
Olga Naumova
Olga Naumova was the wife of renowned Russian-born conductor and double-bassist Serge Koussevitzky, accompanying him through the early part of his musical career.
-
E.
Marfa Lapkina
Marfa Lapkina was a Soviet actress best known for her leading role in Sergei Eisenstein’s silent film "The General Line" (also known as "Old and New").
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd1c0f0081908a6869ee756ec789 |
completed | April 9, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d988a59d6c8190a0e170acfb3af6da |
completed | April 10, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69d98aeb82988190a17b009c74279423 |
completed | April 10, 2026, 11:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98c2aae048190b348e5614ff23f03 |
completed | April 10, 2026, 11:47 p.m. |
Created at: April 8, 2026, 9:11 p.m.