Triple
T24109597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkady Gaidar |
E597327
|
entity |
| Predicate | hasOccupationAsTheme |
P93818
|
FINISHED |
| Object | pioneers |
—
|
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: pioneers | Statement: [Arkady Gaidar, hasOccupationAsTheme, pioneers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOccupationAsTheme Context triple: [Arkady Gaidar, hasOccupationAsTheme, pioneers]
-
A.
hasOccupationTheme
chosen
Indicates that something (such as a work or resource) centrally involves or focuses on a particular occupation or type of work as its main theme.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
hasOccupationFocus
Indicates that an entity’s occupation is primarily centered on, or specialized in, a particular field, role, or area of activity.
-
D.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
E.
careerTheme
Indicates a thematic or conceptual connection between an entity and a particular career-related focus, motif, or overarching professional topic.
- 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_69e288c60f9c8190af948d7354aedbeb |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1de19ce048190aaa3b7b73db50e2f |
completed | April 29, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:02 p.m.