Triple
T25402424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ковальский |
E636460
|
entity |
| Predicate | связан с профессией |
P35215
|
FINISHED |
| Object | кузнец |
—
|
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: кузнец | Statement: [Ковальский, связан с профессией, кузнец]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: связан с профессией Context triple: [Ковальский, связан с профессией, кузнец]
-
A.
relatedProfession
Indicates that two entities have professions that are connected or associated in some meaningful way, such as being in the same field, industry, or professional domain.
-
B.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
-
C.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
D.
конфессия
Indicates that an entity is associated with, belongs to, or is characterized by a particular religious denomination or confession.
-
E.
isAssociatedWithProfessionOfBearer
chosen
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another 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_69e75db361d881908d8701c856da6413 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 1:52 p.m.