Triple
T12936799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian forces briefly occupied parts of Brandenburg |
E309531
|
entity |
| Predicate | natureOfOccupation |
P107596
|
FINISHED |
| Object | brief |
—
|
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: brief | Statement: [Russian forces briefly occupied parts of Brandenburg, natureOfOccupation, brief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: natureOfOccupation Context triple: [Russian forces briefly occupied parts of Brandenburg, natureOfOccupation, brief]
-
A.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
vocationType
Indicates the specific kind or category of occupation, profession, or calling associated with an entity.
-
D.
occupationalNameFor
Indicates that one entity is the name or label used to denote the occupation or profession of another entity.
-
E.
genreOfOccupation
Indicates the specific genre or category that characterizes a particular occupation or professional role.
- F. None of above. chosen
Provenance (4 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e5811f481908178fac6d2e0efcd |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 5:43 p.m.