Triple
T3882672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia |
E92860
|
entity |
| Predicate | variantForm |
P4680
|
FINISHED |
| Object |
Yulia
Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
|
E395351
|
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: Yulia | Statement: [Julia, variantForm, Yulia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yulia Context triple: [Julia, variantForm, Yulia]
-
A.
Svetlana
Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
-
B.
Irina
Irina is a feminine given name commonly used in Slavic and other Eastern European cultures, derived from the Greek name Irene meaning "peace."
-
C.
Galina
Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
D.
Ludmilla
Ludmilla is a coastal suburb of Darwin in Australia's Northern Territory, known for its residential areas and proximity to Fannie Bay.
-
E.
Katerina Tikhonova
Katerina Tikhonova is a Russian academic and business executive widely reported to be one of Vladimir Putin’s daughters, known for her roles in scientific institutions and high-tech investment projects.
- 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: Yulia Triple: [Julia, variantForm, Yulia]
Generated description
Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yulia Target entity description: Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
-
A.
Svetlana
Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
-
B.
Irina
Irina is a feminine given name commonly used in Slavic and other Eastern European cultures, derived from the Greek name Irene meaning "peace."
-
C.
Galina
Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
D.
Ludmilla
Ludmilla is a coastal suburb of Darwin in Australia's Northern Territory, known for its residential areas and proximity to Fannie Bay.
-
E.
Katerina Tikhonova
Katerina Tikhonova is a Russian academic and business executive widely reported to be one of Vladimir Putin’s daughters, known for her roles in scientific institutions and high-tech investment projects.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeec8e8b3481909617ca0e37f8a6d4 |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b512594fa081909ba2afad11f6ea59 |
completed | March 14, 2026, 7:46 a.m. |
| NEDg | Description generation | batch_69b513013db481908f8fb5f56470c0d0 |
completed | March 14, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b513730a308190a04696da9ff901b0 |
completed | March 14, 2026, 7:51 a.m. |
Created at: March 9, 2026, 3:20 p.m.