Triple
T7614599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Briullov |
E172329
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Briullov
Briullov is a Russian surname most famously associated with the 19th-century painter Karl Briullov and his artistic family.
|
E675986
|
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: Briullov | Statement: [Alexander Briullov, familyName, Briullov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Briullov Context triple: [Alexander Briullov, familyName, Briullov]
-
A.
Aleko
Aleko is a popular ski resort area on Vitosha Mountain near Sofia, Bulgaria, known for its winter sports facilities and mountain tourism.
-
B.
Zhores
Zhores is a given name most notably borne by Nobel Prize–winning physicist Zhores Alferov.
-
C.
Eugene Onegin
Eugene Onegin is a classic verse novel by Alexander Pushkin that portrays the life and disillusionment of a jaded Russian aristocrat and is considered a cornerstone of Russian literature.
-
D.
Urusov
Urusov is a Russian noble family name historically associated with princely lineage and notable figures in Russian society.
-
E.
Zhukovsky
Zhukovsky is a town near Moscow, Russia, known as a major center of aviation research and industry.
- 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: Briullov Triple: [Alexander Briullov, familyName, Briullov]
Generated description
Briullov is a Russian surname most famously associated with the 19th-century painter Karl Briullov and his artistic family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Briullov Target entity description: Briullov is a Russian surname most famously associated with the 19th-century painter Karl Briullov and his artistic family.
-
A.
Aleko
Aleko is a popular ski resort area on Vitosha Mountain near Sofia, Bulgaria, known for its winter sports facilities and mountain tourism.
-
B.
Zhores
Zhores is a given name most notably borne by Nobel Prize–winning physicist Zhores Alferov.
-
C.
Eugene Onegin
Eugene Onegin is a classic verse novel by Alexander Pushkin that portrays the life and disillusionment of a jaded Russian aristocrat and is considered a cornerstone of Russian literature.
-
D.
Urusov
Urusov is a Russian noble family name historically associated with princely lineage and notable figures in Russian society.
-
E.
Zhukovsky
Zhukovsky is a town near Moscow, Russia, known as a major center of aviation research and industry.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa4392e881908ed1ab3f64b41600 |
completed | March 27, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8686d16808190bc431c43c0928f6e |
completed | March 28, 2026, 11:46 p.m. |
| NEDg | Description generation | batch_69c8691bf25881909585bb04404f90da |
completed | March 28, 2026, 11:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8698f70a081909633b3b6d7fd45e1 |
completed | March 28, 2026, 11:51 p.m. |
Created at: March 27, 2026, 3:55 p.m.