Triple
T16385568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Олександр Турчинов |
E397912
|
entity |
| Predicate | професійнаДіяльність |
P5863
|
FINISHED |
| Object | політик |
—
|
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: політик | Statement: [Олександр Турчинов, професійнаДіяльність, політик]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: професійнаДіяльність Context triple: [Олександр Турчинов, професійнаДіяльність, політик]
-
A.
professional
chosen
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
B.
professionalWins
Indicates that one entity has achieved a certain number of victories or successes in a professional context, such as in a career, competition, or formal domain.
-
C.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
D.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
E.
professionalism
Indicates that an entity consistently behaves, communicates, and performs tasks in a manner that adheres to accepted standards of competence, ethics, and workplace conduct.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3263c60088190b85a8c02bc3ef315 |
completed | April 18, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:08 a.m.