Triple
T37171702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mykola Zlochevsky |
E920929
|
entity |
| Predicate | sharesBorderWithCareer |
P96605
|
FINISHED |
| Object | Ukrainian energy sector |
—
|
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: Ukrainian energy sector | Statement: [Mykola Zlochevsky, sharesBorderWithCareer, Ukrainian energy sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesBorderWithCareer Context triple: [Mykola Zlochevsky, sharesBorderWithCareer, Ukrainian energy sector]
-
A.
sharesProfessionWith
Indicates that two entities have the same profession or occupational role.
-
B.
associatedWithCareerOf
chosen
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
-
C.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
-
D.
partnerInCareerOf
Indicates a relationship where one entity is a professional or career partner of another, collaborating or sharing a joint career path or venture.
-
E.
supportedCareerOf
Indicates that one entity provided assistance, resources, or endorsement that helped establish or advance another entity’s career.
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a00b34364448190b8c9948d5a24d845 |
completed | May 10, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_6a00b2e4f13c819081bac7d763c414ad |
completed | May 10, 2026, 4:31 p.m. |
Created at: May 3, 2026, 4:15 p.m.