Triple
T23928778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Лазарь Маркович Лисицкий |
E602432
|
entity |
| Predicate | профессия |
P55498
|
FINISHED |
| Object | художник |
—
|
LITERAL FINISHED |
How this triple was built (2 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: художник | Statement: [Лазарь Маркович Лисицкий, профессия, художник]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: профессия Context triple: [Лазарь Маркович Лисицкий, профессия, художник]
-
A.
конфессия
Indicates that an entity is associated with, belongs to, or is characterized by a particular religious denomination or confession.
-
B.
leftProfession
Indicates that an entity has stopped or abandoned a particular profession or occupation they previously held.
-
C.
natureOfOccupation
Indicates the type or character of a person's occupation, describing what kind of work or role it is rather than who performs it.
-
D.
occupationAspiration
Indicates a person's desired or intended future occupation or career goal.
-
E.
careerType
chosen
Indicates the kind or category of professional occupation or career path associated with an entity.
- F. None of above.
Provenance (3 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_69e2953b928c819095395fa87baca583 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cf1efb348190b4cbb32b3b6c9ae4 |
completed | April 29, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:54 p.m.