Triple
T14841745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BPS-16 |
E348980
|
entity |
| Predicate | typicalDesignation |
P116039
|
FINISHED |
| Object | Assistant |
—
|
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: Assistant | Statement: [BPS-16, typicalDesignation, Assistant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDesignation Context triple: [BPS-16, typicalDesignation, Assistant]
-
A.
systemDesignation
Indicates that an entity has been assigned a specific formal label or identifier within a defined system or framework.
-
B.
exampleDesignation
Indicates that one entity is identified or labeled as a representative or illustrative instance of another entity.
-
C.
prototypeDesignation
Indicates that one entity is designated or identified as a prototype version or exemplar of another entity.
-
D.
designatorType
Indicates the specific role or category of a designator used to identify or reference an entity within a system or context.
-
E.
alternateDesignation
Indicates that one entity serves as an alternative name, label, or identifier for another entity.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded28fa49c81908d1059e6cafd607f |
completed | April 14, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69de8c13418c819088ff9905ace1416a |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de90806f3881908fcbfec5bd4ab4d2 |
completed | April 14, 2026, 7:07 p.m. |
Created at: April 10, 2026, 1:53 a.m.